Project Titles 2016-2017

                                                                     Project Titles 2016-17

 

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CSE/IT (IEEE 2015):(JAVA/NS-2)        

ECE (IEEE 2015):(EMBEDDED SYSTEM)     
ECE (IEEE 2015):(MATLAB)              
EEE (IEEE 2015):(PED,PS,EM)           
ALL TITLES (IEEE 2015-ALL DEPARTMENTS):

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  ECE (Diploma)                                           

  EEE (Diploma)                                

  CSE (Diploma)                                

   MECHANICAL(Diploma)                       

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                                                                     Project Titles 2014 

CSE/IT (IEEE 2014):(JAVA/DotNet)                     CSE (IEEE 2014):(ANDROID)                             

EEE (IEEE 2014)                                       ECE (IEEE 2014):(EMBEDDED SYSTEM)                     

ECE (IEEE 2014):(MATLAB IMAGE PROCESSING,DSP,COMMUNICATION)          
ECE (IEEE 2014):(ANDROID)                            
MECHANICAL (IEEE 2014):                              

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To get any base papers from this list send your details like college name,department,contact number to our mail id spectrumpondicherry@gmail.com.

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JAVA/NS-2

APPENDIX:

D                  DotNet

J                    Java

IP        Image Processing

DM     DataMining

NS       Network Security

NW     Networking

MC     Mobile Computing

SC       Service Computing

PD      Parallel distribution

CC     Cloud Computing

S.No	Code	Title	Year		Abstract
1	JCCZ-01	AuditFree Cloud Storage via Deniable Attribute based Encryption	IEEE-2015		Cloud storage services have become increasingly popular. Because of the importance of privacy, many cloud storage encryption schemes have been proposed to protect data from those who do not have access. All such schemes assumed that cloud storage providers are safe and cannot be hacked; however, in practice, some authorities (i.e., coercers) may force cloud storage providers to reveal user secrets or confidential data on the cloud, thus altogether circumventing storage encryption schemes. In this paper, we present our design for a new cloud storage encryption scheme that enables cloud storage providers to create convincing fake user secrets to protect user privacy. Since coercers cannot tell if obtained secrets are true or not, the cloud storage providers ensure that user privacy is still securely protected.
2	JCCZ-02	CHARM A Cost efficient Multi cloud Data Hosting Scheme with High Availability	IEEE-2015		Nowadays, more and more enterprises and organizations are hosting their data into the cloud, in order to reduce the IT maintenance cost and enhance the data reliability. However, facing the numerous cloud vendors as well as their heterogenous pricing policies, customers may well be perplexed with which cloud(s) are suitable for storing their data and what hosting strategy is cheaper. The general status quo is that customers usually put their data into a single cloud (which is subject to the vendor lock-in risk) and then simply trust to luck. Based on comprehensive analysis of various state-of-the-art cloud vendors, this paper proposes a novel data hosting scheme (named CHARM) which integrates two key functions desired. The first is selecting several suitable clouds and an appropriate redundancy strategy to store data with minimized monetary cost and guaranteed availability. The second is triggering a transition process to re-distribute data according to the variations of data access pattern and pricing of clouds. We evaluate the performance of CHARM using both trace-driven simulations and prototype experiments. The results show that compared with the major existing schemes, CHARM not only saves around 20% of monetary cost but also exhibits sound adaptability to data and price adjustments. Index Terms—Multi-cloud; data hosting; cloud storage.
3	JCCZ-03	Enabling Cloud Storage Auditing with Key Exposure Resistance	IEEE-2015		Cloud storage auditing is viewed as an important service to verify the integrity of the data in public cloud. Current auditing protocols are all based on the assumption that the client’s secret key for auditing is absolutely secure. However, such assumption may not always be held, due to the possibly weak sense of security and/or low security settings at the client. If such a secret key for auditing is exposed, most of the current auditing protocols would inevitably become unable to work. In this paper, we focus on this new aspect of cloud storage auditing. We investigate how to reduce the damage of the client’s key exposure in cloud storage auditing, and give the first practical solution for this new problem setting. We formalize the definition and the security model of auditing protocol with key-exposure resilience and propose such a protocol. In our design, we employ the binary tree structure and the pre-order traversal technique to update the secret keys for the client. We also develop a novel authenticator construction to support the forward security and the property of blockless verifiability. The security proof and the performance analysis show that our proposed protocol is secure and efficient.
4	JCCZ-04	MobiContext_Cloud	IEEE-2015		In recent years, recommendation systems have seen significant evolution in the field of knowledge engineering. Most of the existing recommendation systems based their models on collaborative filtering approaches that make them simple to implement. However, performance of most of the existing collaborative filtering based recommendation system suffers due to the challenges, such as: (a) cold start, (b) data sparseness, and (c) scalability. Moreover, recommendation problem is often characterized by the presence of many conflicting objectives or decision variables, such as users’ preferences and venue closeness. In this paper, we proposed MobiContext, a hybrid cloud based Bi Objective Recommendation Framework (BORF) for mobile social networks. The MobiContext utilizes multi objective optimization techniques to generate personalized recommendations. To address the issues pertaining to cold start and data sparseness, the BORF performs data preprocessing by using the Hub Average (HA) inference model. Moreover, the Weighted Sum Approach (WSA) is implemented for scalar optimization and an evolutionary algorithm (NSGAII) is applied for vector optimization to provide optimal suggestions to the users about a venue.
5	JCCZ-05	OPoR Enabling Proof of Retrievability in Cloud Computing with Resource Constrained Devices	IEEE-2015		Cloud Computing moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. In this work, we study the problem of ensuring the integrity of data storage in Cloud Computing. To reduce the computational cost at user side during the integrity verification of their data, the notion of public verifiability has been proposed. However, the challenge is that the computational burden is too huge for the users with resource-constrained devices to compute the public authentication tags of file blocks. To tackle the challenge, we propose OPoR, a new cloud storage scheme involving a cloud storage server and a cloud audit server, where the latter is assumed to be semi-honest. In particular, we consider the task of allowing the cloud audit server, on behalf of the cloud users, to pre-process the data before uploading to the cloud storage server and later verifying the data integrity. OPoR outsources the heavy computation of the tag generation to the cloud audit server and eliminates the involvement of user in the auditing and in the preprocessing phases. Furthermore, we strengthen the Proof of Retrievabiliy (PoR) model to support dynamic data operations, as well as ensure security against reset attacks launched by the cloud storage server in the upload phase.
6	JCCZ-06	Privacy-Preserving Public Auditing for	IEEE-2015		To protect outsourced data in cloud storage against corruptions, adding fault tolerance to cloud storage together with data integrity checking and failure reparation becomes critical. Recently, regenerating codes have gained popularity due to their lower repair bandwidth while providing fault tolerance. Existing remote checking methods for regenerating-coded data only provide private auditing, requiring data owners to always stay online and handle auditing, as well as repairing, which is sometimes impractical. In this paper, we propose a public auditing scheme for the regenerating-code-based cloud storage. To solve the regeneration problem of failed authenticators in the absence of data owners, we introduce a proxy, which is privileged to regenerate the authenticators, into the traditional public auditing system model. Moreover, we design a novel public verifiable authenticator, which is generated by a couple of keys and can be regenerated using partial keys. Thus, our scheme can completely release data owners from online burden. In addition, we randomize the encode coefficients with a pseudorandom function to preserve data privacy. Extensive security analysis shows that our scheme is provable secure under random oracle model and experimental evaluation indicates that our scheme is highly efficient .
7	JCCZ-07	Profit Maximization Scheme	IEEE-2015		As an effective and efficient way to provide computing resources and services to customers on demand, cloud computing has become more and more popular. From cloud service providers’ perspective, profit is one of the most important considerations, and it is mainly determined by the configuration of a cloud service platform under given market demand. However, a single long-term renting scheme is usually adopted to configure a cloud platform, which cannot guarantee the service quality but leads to serious resource waste. In this paper, a double resource renting scheme is designed firstly in which short-term renting and long-term renting are combined aiming at the existing issues. This double renting scheme can effectively guarantee the quality of service of all requests and reduce the resource waste greatly. Secondly, a service system is considered as an M/M/m+D queuing model and the performance indicators that affect the profit of our double renting scheme are analyzed, e.g., the average charge, the ratio of requests that need temporary servers, and so forth. Thirdly, a profit maximization problem is formulated for the double renting scheme and the optimized configuration of a cloud platform is obtained by solving the profit maximization problem.
8	JCCZ-08	Reactive Resource Provisioning Heuristics for	IEEE-2015		The need for low latency analysis over high-velocity data streams motivates the need for distributed continuous dataflow systems. Contemporary stream processing systems use simple techniques to scale on elastic cloud resources to handle variable data rates. However, application QoS is also impacted by variability in resource performance exhibited by clouds and hence necessitates “dynamic dataflows” which utilize alternate tasks as additional control over the dataflow’s cost and QoS. Further, we formalize an optimization problem to represent deployment and runtime resource provisioning that allows us to balance the application’s QoS, value, and the resource cost. We propose two greedy heuristics, centralized and sharded, based on the variable-sized bin packing algorithm and compare against a Genetic Algorithm (GA) based heuristic that gives a near-optimal solution. A large-scale simulation study, using the Linear Road Benchmark and VM performance traces from the AWS public cloud, shows that while GA-based heuristic provides a better quality schedule, the greedy heuristics are more practical, and can intelligently utilize cloud elasticity to mitigate the effect of variability, both in input data rates and cloud resource performance, to meet the QoS of fast data applications.
9	JCCZ-09	SAE Toward Efficient Cloud Data Analysis	IEEE-2015		Social network analysis is used to extract features of human communities and proves to be very instrumental in a variety of scientific domains. The dataset of a social network is often so large that a cloud data analysis service, in which the computation is performed on a parallel platform in the could, becomes a good choice for researchers not experienced in parallel programming. In the cloud, a primary challenge to efficient data analysis is the computation and communication skew (i.e., load imbalance) among computers caused by humanity’s group behavior (e.g., bandwagon effect). Traditional load balancing techniques either require significant effort to re-balance loads on the nodes, or cannot well cope with stragglers. In this paper, we propose a general straggler-aware execution approach, SAE, to support the analysis service in the cloud. It offers a novel computational decomposition method that factors straggling feature extraction processes into more fine-grained sub-processes, which are then distributed over clusters of computers for parallel execution. Experimental results show that SAE can speed up the analysis by up to 1.77 times compared with state-of-the-art solutions.
10	JCCZ-10	Service Operatoraware Trust Scheme for Resource	IEEE-2015		This paper proposes a service operator-aware trust scheme (SOTS) for resource matchmaking across multiple clouds. Through analyzing the built-in relationship between the users, the broker, and the service resources, this paper proposes a middleware framework of trust management that can effectively reduce user burden and improve system dependability. Based on multi-dimensional resource service operators, we model the problem of trust evaluation as a process of multi-attribute decision-making, and develop an adaptive trust evaluation approach based on information entropy theory. This adaptive approach can overcome the limitations of traditional trust schemes, whereby the trusted operators are weighted manually or subjectively. As a result, using SOTS, the broker can efficiently and accurately prepare the most trusted resources in advance, and thus provide more dependable resources to users. Our experiments yield interesting and meaningful observations that can facilitate the effective utilization of SOTS in a large-scale multi-cloud environment.
11	JCCZ-11	Towards Optimized Fine Grained Pricing of	IEEE-2015		Although many pricing schemes in IaaS platform are already proposed with pay-as-you-go and subscription/spot market policy to guarantee service level agreement, it is still inevitable to suffer from wasteful payment because of coarsegrained pricing scheme. In this paper, we investigate an optimized fine-grained and fair pricing scheme. Two tough issues are addressed: (1) the profits of resource providers and customers often contradict mutually; (2) VM-maintenance overhead like startup cost is often too huge to be neglected. Not only can we derive an optimal price in the acceptable price range that satisfies both customers and providers simultaneously, but we also find a best-fit billing cycle to maximize social welfare (i.e., the sum of the cost reductions for all customers and the revenue gained by the provider). We carefully evaluate the proposed optimized fine-grained pricing scheme with two large-scale real-world production traces (one from Grid Workload Archive and the other from Google data center). We compare the new scheme to classic coarse-grained hourly pricing scheme in experiments and find that customers and providers can both benefit from our new approach. The maximum social welfare can be increased up to 72:98% and 48:15% with respect to DAS-2 trace and Google trace respectively.
12	JCCZ-12	Understanding the Performance and	IEEE-2015		Commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require   significant resources, however not all scientists have access to sufficien  high  end computing systems. Cloud computing has  gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as   DIfferent  infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable  performance per money spent. This work provides a comprehensive evaluation of EC2 cloud in different aspects. We first analyze the potentials  of the cloud by evaluating the raw performance of different services of AWS such as compute, memory, network and I /O. Based  on the findings on the raw performance, we then evaluate the performance of the scientific applications running in the cloud.  Finally, we compare the performance of AWS with a private cloud, in order to find the root cause of its limitations while  running  scientific applications. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the  cloud in terms of both raw performance and scientific applications performance Furthermore, we evaluate other  services  including S3, EBS and DynamoDB among many AWS services in order to assess the abilities of those to be used by scientific  applications and frameworks. We also evaluate a real scientific compng application through the Swift parallel scripting System at scale.
13	JDMZ-01	Anonymizing Collections of Tree Struct Data- Data Engg	IEEE-2015		Collections of real-world data usually have implicit or explicit structural relations. For example, databases link records through foreign keys, and XML documents express associations between different values through syntax. Privacy preservation, until now, has focused either on data with a very simple structure, e.g. relational tables, or on data with very complex structure e.g. social network graphs, but has ignored intermediate cases, which are the most frequent in practice. In this work, we focus on tree structured data. Such data stem from various applications, even when the structure is not directly reflected in the syntax, e.g. XML documents. A characteristic case is a database where information about a single person is scattered amongst different tables that are associated through foreign keys. The paper defines k(m;n)-anonymity, which provides protection against identity disclosure and proposes a greedy anonymization heuristic that is able to sanitize large datasets. The algorithm and the quality of the anonymization are evaluated experimentally.
14	JDMZ-02	FOCS Fast Overlapped Community Search	IEEE-2015		However, most of the existing algorithms that detect overlapping communities assume that the communities are denser than their surrounding regions and falsely identify overlaps as communities. Further, many of these algorithms are computationally demanding and thus, do not scale reasonably with varying network sizes. In this article, we propose FOCS (Fast Overlapped Community Search), an algorithm that accounts for local connectedness in order to identify overlapped communities. FOCS is shown to be linear in number of edges and nodes. It additionally gains in speed via simultaneous selection of multiple near-best communities rather than merely the best, at each iteration. FOCS outperforms some popular overlapped community finding algorithms in terms of
15	JDMZ-03	Making Digital Artifacts_Data Engg	IEEE-2015		The current Web has no general mechanisms to make digital artifacts — such as datasets, code, texts, and images — verifiable and permanent. For digital artifacts that are supposed to be immutable, there is moreover no commonly accepted method to enforce this immutability. These shortcomings have a serious negative impact on the ability to reproduce the results of processes that rely onWeb resources, which in turn heavily impacts areas such as science where reproducibility is important. To solve this problem, we propose trusty URIs containing cryptographic hash values. We show how trusty URIs can be used for the verification of digital artifacts, in a manner that is independent of the serialization format in the case of structured data files such as nano publications.
16	JDMZ-04	Privacy Policy Inference of User-Uploaded	IEEE-2015		With the increasing volume of images users share through social sites, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. We propose a two-level framework which according to the user’s available history on the site, determines the best available privacy policy for the user’s images being uploaded. Our solution relies on an image classification framework for image categories which may be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to users’ social features.
17	JDMZ-05	RRW - A Robust and Reversible Watermarking	IEEE-2015		Advancement in information technology is playing an increasing role in the use of information systems comprising relational databases. These databases are used effectively in collaborative environments for information extraction; consequently, they are vulnerable to security threats concerning ownership rights and data tampering. Watermarking is advocated to enforce ownership rights over shared relational data and for providing a means for tackling data tampering. When ownership rights are enforced using watermarking, the underlying data undergoes certain modifications; as a result of which, the data quality gets compromised. Reversible watermarking is employed to ensure data quality along-with data recovery. However, such techniques are usually not robust against malicious attacks and do not provide any mechanism to selectively watermark a particular attribute by taking into account its role in knowledge discovery. Therefore, reversible watermarking is required that ensures; (i) watermark encoding and decoding by accounting for the role of all the features in knowledge discovery; and, (ii) original data recovery in the presence of active malicious attacks.
18	JDMZ-06	Sparsity Learning Formulations for Mining	IEEE-2015		Traditional clustering and feature selection methods consider the data matrix as static. However, the data matrices evolve smoothly over time in many applications. A simple approach to learn from these time-evolving data matrices is to analyze them separately. Such strategy ignores the time-dependent nature of the underlying data. In this paper, we propose two formulations for evolutionary co-clustering and feature selection based on the fused Lasso regularization. The evolutionary co-clustering formulation is able to identify smoothly varying hidden block structures embedded into the matrices along the temporal dimension. Our formulation is very flexible and allows for imposing smoothness constraints over only one dimension of the data matrices. The evolutionary feature selection formulation can uncover shared features in clustering from time-evolving data matrices. We show that the optimization problems involved are non-convex, non-smooth and non-separable. To compute the solutions efficiently, we develop a two-step procedure that optimizes the objective function iteratively. We evaluate the proposed formulations using the Allen Developing Mouse Brain Atlas data. Results show that our formulations consistently outperform prior methods.
19	JDMZ-07	Structured Learning_Knowledge Discovery	IEEE-2015		Social identity linkage across different social media platforms is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. In this paper, we propose a solution framework, HYDRA, which consists of three key steps: (I) we model heterogeneous behavior by long-term topical distribution analysis and multi-resolution temporal behavior matching against high noise and information missing, and the behavior similarity are described by multi-dimensional similarity vector for each user pair; (II) we build structure consistency models to maximize the structure and behavior consistency on users’ core social structure across different platforms, thus the task of identity linkage can be performed on groups of users, which is beyond the individual level linkage in previous study; and (III) we propose a normalized-margin-based linkage function formulation, and learn the linkage function by multi-objective optimization where both supervised pair-wise linkage function learning and structure consistency maximization are conducted towards a unified Pareto optimal solution. The model is able to deal with drastic information missing, and avoid the curse-of-dimensionality in handling high dimensional sparse representation.
20	JDMZ-08	Subgraph Matching with Set Similarity	IEEE-2015		In real-world graphs such as social networks, Semantic Web and biological networks, each vertex usually contains rich information, which can be modeled by a set of tokens or elements. In this paper, we study a subgraph matching with set similarity (SMS2) query over a large graph database, which retrieves subgraphs that are structurally isomorphic to the query graph, and meanwhile satisfy the condition of vertex pair matching with the (dynamic) weighted set similarity. To efficiently process the SMS2 query, this paper designs a novel lattice-based index for data graph, and lightweight signatures for both query vertices and data vertices. Based on the index and signatures, we propose an efficient two-phase pruning strategy including set similarity pruning and structure-based pruning, which exploits the unique features of both (dynamic) weighted set similarity and graph topology. We also propose an efficient dominating-set-based subgraph matching algorithm guided by a dominating set selection algorithm to achieve better query performance. Extensive experiments on both real and synthetic datasets demonstrate that our method outperforms state-of-the-art methods by an order of magnitude.
21	JDMZ-09	The Impact of View Histories on Edit Recommendations	IEEE-2015		Recommendation systems are intended to increase developer productivity by recommending files to edit. These systems mine association rules in software revision histories. However, mining coarse  grained rules using only edit histories produces recommendations with low accuracy, and can only produce recommendations after a developer edits a file. In this work, we explore the use of finer grained association rules, based on the insight that view histories help characterize the contexts of files to edit. To leverage this additional context and fine grained association rules, we have developed MI, a recommendation system extending ROSE, an existing edit based recommendation system. We then conducted a comparative simulation of ROSE and MI using the interaction histories stored in the Eclipse Bugzilla system. The simulation demonstrates that MI predicts the files to edit with significantly higher recommendation accuracy than ROSE (about 63% over 35%), and makes recommendations earlier, often before developers begin editing. Our results clearly demonstrate the value of considering both views and edits in systems to recommend files to edit, and results in more accurate, earlier, and more flexible recommendations.
22	JDMZ-10	Towards Effective Bug Triage with Software Data Reduction Techniques	IEEE-2015		Software companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer to a new bug. To decrease the time cost in manual work, text classification techniques are applied to conduct automatic bug triage. In this paper, we address the problem of data reduction for bug triage, i.e., how to reduce the scale and improve the quality of bug data. We combine instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word dimension. To determine the order of applying instance selection and feature selection, we extract attributes from historical bug data sets and build a predictive model for a new bug data set. We empirically investigate the performance of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and Mozilla. The results show that our data reduction can effectively reduce the data scale and improve the accuracy of bug triage. Our work provides an approach to leveraging techniques on data processing to form reduced and high-quality bug data in software development and maintenance.
23	JIPZ-01	Multiview Alignment Hashing for Efficient Image	IEEE-2015		Hashing is a popular and efficient method for nearest neighbor search in large-scale data spaces, by embedding high-dimensional feature descriptors into a similarity preserving Hamming space with a low dimension. For most hashing methods, the performance of retrieval heavily depends on the choice of the high-dimensional feature descriptor. Furthermore, a single type of feature cannot be descriptive enough for different images when it is used for hashing. Thus, how to combine multiple representations for learning effective hashing functions is an imminent task. In this paper, we present a novel unsupervised Multiview Alignment Hashing (MAH) approach based on Regularized Kernel Nonnegative Matrix Factorization (RKNMF),
24	JIPZ-02	YouTube Video Promotion by Cross-network	IEEE-2015		The emergence and rapid proliferation of various social media networks have reshaped the way how video contents are generated, distributed and consumed in traditional video sharing portals. Nowadays, online videos can be accessed from far beyond the internal mechanisms of the video sharing portals, such as internal search and front page highlight. Recent studies have found that external referrers, such as external search engines and other social media websites, arise to be the new and important portals to Lead users to online videos. In this paper, we introduce a novel cross-network collaborative application to help drive the online traffic for given videos in traditional video portal YouTube by leveraging the high propagation efficiency of the popular Twitter followees.
25	JMCZ-01	Modelling and Analysis_Mob Comp	IEEE-2015		—In opportunistic networks, direct communication between mobile devices is used to extend the set of services accessible through cellular or WiFi networks. Mobility patterns and their impact in such networks have been extensively studied. In contrast, this has not been the case with communication traffic patterns, where homogeneous traffic between all nodes is usually assumed. This assumption is generally not true, as node mobility and social characteristics can significantly affect the end-to-end traffic demand between them. To this end, in this paper we explore the joint effect of traffic patterns and node mobility on the performance of popular forwarding mechanisms, both analytically and through simulations. Among the different insights stemming from our analysis, we identify conditions under which heterogeneity renders the added value of using extra relays more/less useful. Furthermore, we confirm the intuition that an increasing amount of heterogeneity closes the performance gap between different forwarding policies, making endto- end routing more challenging in some cases.
26	JMCZ-02	Towards Information Diffusion in Mobile Social	IEEE-2015		The emerging of mobile social networks opens opportunities for viral marketing. However, before fully utilizing mobile social networks as a platform for viral marketing, many challenges have to be addressed. In this paper, we address the problem of identifying a small number of individuals through whom the information can be diffused to the network as soon as possible, referred to as the diffusion minimization problem. Diffusion minimization under the probabilistic diffusion model can be formulated as an asymmetric k- center problem which is NP-hard, and the best known approximation algorithm for the asymmetric k-center problem has approximation ratio of log_ n and time complexity O(n5). Clearly, the performance and the time complexity of the approximation algorithm are not satisfiable in large-scale mobile social networks.
27	JMMZ-01	Color imaging_Multimedia	IEEE-2015		Multimedia data with associated semantics is omnipresent in today’s social online platforms in the form of keywords, user comments, and so forth. This article presents a statistical framework designed to infer knowledge in the imaging domain from the semantic domain. Note that this is the reverse direction of common computer vision applications. The framework relates keywords to image characteristics using a statistical significance test. It scales to millions of images and hundreds of thousands of keywords. We demonstrate the usefulness of the statistical framework with three color imaging applications: 1) semantic image enhancement: re-render an image in order to adapt it to its semantic context; 2) color naming: find the color triplet for a given color name; and 3) color palettes: find a palette of colors that best represents a given arbitrary semantic context and that satisfies established harmony constraints.
28	JPDZ-01	Secure Distributed Deduplication Systems with Improved Reliability -01-Secure Distributed Deduplication Systems with Improved Reliability	IEEE-2015		Data deduplication is a technique for eliminating duplicate copies of data, and has been widely used in cloud storage to reduce storage space and upload bandwidth. However, there is only one copy for each file stored in cloud even if such a file is owned by a huge number of users. As a result, deduplication system improves storage utilization while reducing reliability. Furthermore, the challenge of privacy for sensitive data also arises when they are outsourced by users to cloud. Aiming to address the above security challenges, this paper makes the first attempt to formalize the notion of distributed reliable deduplication system. We propose new distributed deduplication systems with higher reliability in which the data chunks are distributed across multiple cloud servers.
29	JPDZ-02	Service Operatoraware Trust Scheme for Resource	IEEE-2015		This paper proposes a service operator-aware trust scheme (SOTS) for resource matchmaking across multiple clouds. Through analyzing the built-in relationship between the users, the broker, and the service resources, this paper proposes a middleware framework of trust management that can effectively reduce user burden and improve system dependability. Based on multi-dimensional resource service operators, we model the problem of trust evaluation as a process of multi-attribute decision-making, and develop an adaptive trust evaluation approach based on information entropy theory. This adaptive approach can overcome the limitations of traditional trust schemes, whereby the trusted operators are weighted manually or subjectively. As a result, using SOTS, the broker can efficiently and accurately prepare the most trusted resources in advance, and thus provide more dependable resources to users. Our experiments yield interesting and meaningful observations that can facilitate the effective utilization of SOTS in a large-scale multi-cloud environment.
30	JSCZ-01	A Trust-Aware Service Brokering Scheme	IEEE-2015		Oriented by requirement of trust management in multiple cloud environment, this paper presents T-broker, a trustaware service brokering scheme for efficient matching cloud services (or resources) to satisfy various user requests. First, a trusted third party-based service brokering architecture is proposed for multiple cloud environment, in which the T-broker acts as a middleware for cloud trust management and service matching. Then, T-broker uses a hybrid and adaptive trust model to compute the overall trust degree of service resources, in which trust is defined as a fusion evaluation result from adaptively combining the direct monitored evidence with the social feedback of the service resources. More importantly, T-broker uses the maximizing deviation method to compute the direct experience based on multiple key trusted attributes of service resources, which can overcome the limitations of traditional trust schemes, in which the trusted attributes are weighted manually or subjectively. Finally, T-broker uses a lightweight feedback mechanism, which can effectively reduce networking risk and improve system efficiency. The experimental results show that, compared with the existing approaches, our T-broker yields very good results in many typical cases, and the proposed system is robust to deal with various numbers of dynamic service behavior from multiple cloud sites.
31	JSCZ-02	Collusion-Tolerable Privacy-Preserving Sum and	IEEE-2015		Much research has been conducted to securely outsource multiple parties’ data aggregation to an untrusted aggregator without disclosing each individual’s privately owned data, or to enable multiple parties to jointly aggregate their data while preserving privacy. However, those works either require secure pair-wise communication channels or suffer from high complexity. In this paper, we consider how an external aggregator or multiple parties can learn some algebraic statistics (e.g., sum, product) over participants’ privately owned data while preserving the data privacy. We assume all channels are subject to eavesdropping attacks, and all the communications throughout the aggregation are open to others. We first propose several protocols that successfully guarantee data privacy under semi-honest model, and then present advanced protocols which tolerate up to k passive adversaries who do not try to tamper the computation. Under this weak assumption, we limit both the communication and computation complexity of each participant to a small constant. At the end, we present applications which solve several interesting problems via our protocols.
32	JSCZ-03	Control Cloud Data Access Privilege and Anonymity With Fully Anonymous Attribute-Based Encryption	IEEE-2015		Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semi anonymous privilege control scheme Anony Control to address not only the data privacy, but also the user identity privacy in existing access control schemes. Anony Control decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the Anony Control-F, which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both Anony  Control and Anony Control-F are secure under the decisional bilinear Diffie–Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.
33	JSCZ-04	Data Lineage in Malicious Environments	IEEE-2015		Intentional or unintentional leakage of confidential data is undoubtedly one of the most severe security threats that organizations face in the digital era. The threat now extends to our personal lives: a plethora of personal information is available to social networks and smartphone providers and is indirectly transferred to untrustworthy third party and fourth party applications. In this work, we present a generic data lineage framework LIME for data flow across multiple entities that take two characteristic, principal roles (i.e., owner and consumer). We define the exact security guarantees required by such a data lineage mechanism toward identification of a guilty entity, and identify the simplifying non-repudiation and honesty assumptions. We then develop and analyze a novel accountable data transfer protocol between two entities within a malicious environment by building upon oblivious transfer, robust watermarking, and signature primitives. Finally, we perform an experimental evaluation to demonstrate the practicality of our protocol and apply our framework to the important data leakage scenarios of data outsourcing and social networks. In general, we consider LIME , our lineage framework for data transfer, to be an key step towards achieving accountability by design.
34	JSCZ-05	Enabling Cloud Storage Auditing with	IEEE-2015		Cloud storage auditing is viewed as an important service to verify the integrity of the data in public cloud. Current auditing protocols are all based on the assumption that the client’s secret key for auditing is absolutely secure. However, such assumption may not always be held, due to the possibly weak sense of security and/or low security settings at the client. If such a secret key for auditing is exposed, most of the current auditing protocols would inevitably become unable to work. In this paper, we focus on this new aspect of cloud storage auditing. We investigate how to reduce the damage of the client’s key exposure in cloud storage auditing, and give the first practical solution for this new problem setting. We formalize the definition and the security model of auditing protocol with key-exposure resilience and propose such a protocol. In our design, we employ the binary tree structure and the pre-order traversal technique to update the secret keys for the client. We also develop a novel authenticator construction to support the forward security and the property of blockless verifiability. The security proof and the performance analysis show that our proposed protocol is secure and efficient.
35	JSCZ-06	Formalization and Verification_Cybernetics	IEEE-2015		Group behavior interactions, such as multirobot teamwork and group communications in social networks, are widely seen in both natural, social, and artificial behavior related applications. Behavior interactions in a group are often associated with varying coupling relationships, for instance, conjunction or disjunction. Such coupling relationships challenge existing behavior representation methods, because they involve multiple behaviors from different actors, constraints on the interactions, and behavior evolution. In addition, the quality of behavior interactions are not checked through verification techniques. In this paper, we propose an ontology-based behavior modeling and checking system (OntoB for short) to explicitly represent and verify complex behavior relationships, aggregations, and constraints. The OntoB system provides both a visual behavior model and an abstract behavior tuple to capture behavioral elements, as well as building blocks. It formalizes various intra-coupled interactions (behaviors conducted by the same actor) via transition systems (TSs), and inter-coupled behavior aggregations (behaviors conducted by different actors) from temporal, inferential, and party-based perspectives.
36	JSCZ-07	Group Key Agreement with Local Connectivity	IEEE-2015		In this paper, we study a group key agreement problem where a user is only aware of his neighbors while the connectivity graph is arbitrary. In our problem, there is no centralized initialization for users. A group key agreement with these features is very suitable for social networks. Under our setting, we construct two efficient protocols with passive security. We obtain lower bounds on the round complexity for this type of protocol, which demonstrates that our constructions are round efficient. Finally, we construct an actively secure protocol from a passively secure one.
37	JSCZ-08	Privacy-Preserving Public Auditing for	IEEE-2015	To protect outsourced data in cloud storage against corruptions, adding fault tolerance to cloud storage together with data integrity checking and failure reparation becomes critical. Recently, regenerating codes have gained popularity due to their lower repair bandwidth while providing fault tolerance. Existing remote checking methods for regenerating-coded data only provide private auditing, requiring data owners to always stay online and handle auditing, as well as repairing, which is sometimes impractical. In this paper, we propose a public auditing scheme for the regenerating-code-based cloud storage. To solve the regeneration problem of failed authenticators in the absence of data owners, we introduce a proxy, which is privileged to regenerate the authenticators, into the traditional public auditing system model.
38	JSEZ-01	Impact of view_DM	IEEE-2015		Recommendation systems are intended to increase developer productivity by recommending files to edit. These systems mine association rules in software revision histories. However, mining coarse-grained rules using only edit histories produces recommendations with low accuracy, and can only produce recommendations after a developer edits a file. In this work, we explore the use of fine-grained association rules, based on the insight that view histories help characterize the contexts of files to edit. To leverage this additional context and fine-grained association rules, we have developed MI, a recommendation system extending ROSE, an existing edit based recommendation system. We then conducted a comparative simulation of ROSE and MI using the interaction histories stored in the Eclipse Bugzilla system. The simulation demonstrates that MI predicts the files to edit with significantly higher recommendation accuracy than ROSE (about 63% over 35%), and makes recommendations earlier, often before developers begin editing. Our results clearly demonstrate the value of considering both views and edits in systems to recommend files to edit, and results in more accurate, earlier, and more flexible recommendations.
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39	NSZ-01	A Distributed Fault-Tolerant Topology Control Algorithm for Heterogeneous Wireless Sensor Networks	IEEE-2015		This paper introduces a distributed fault-tolerant topology control algorithm, called the Disjoint Path Vector (DPV), for heterogeneous wireless sensor networks composed of a large number of sensor nodes with limited energy and computing capability and several supernodes with unlimited energy resources. The DPV algorithm addresses the k-degree Anycast Topology Control problem where the main objective is to assign each sensor’s transmission range such that each has at least k-vertex-disjoint paths to supernodes and the total power consumption is minimum. The resulting topologies are tolerant to k _ 1 node failures in the worst case. We prove the correctness of our approach by showing that topologies generated by DPV are guaranteed to satisfy k-vertex supernode connectivity. Our simulations show that the DPV algorithm achieves up to 4-fold reduction in total transmission power required in the network and 2-fold reduction in maximum transmission power required in a node compared to existing solutions.
40	NSZ-02	Adaptive Algorithms for Diagnosing Large-Scale Failures in Computer Networks	IEEE-2015		We propose a greedy algorithm, Cluster-MAX-COVERAGE (CMC), to efficiently diagnose large-scale clustered failures. We primarily address the challenge of determining faults with incomplete symptoms. CMC makes novel use of both positive and negative symptoms to output a hypothesis list with a low number of false negatives and false positives quickly. CMC requires reports from about half as many nodes as other existing algorithms to determine failures with 100 percent accuracy. Moreover, CMC accomplishes this gain significantly faster (sometimes by two orders of magnitude) than an algorithm that matches its accuracy. When there are fewer positive and negative symptoms at a reporting node, CMC performs much better than existing algorithms. We also propose an adaptive algorithm called Adaptive-MAX-COVERAGE (AMC) that performs efficiently during both independent and clustered failures. During a series of failures that include both independent and clustered, AMC results in a reduced number of false negatives and false positives.
41	NSZ-03	Delay Optimization and Cross-Layer Design in Multihop Wireless Networks With Network Coding and Successive Interference Cancelation	IEEE-2015		Network coding (NC) and multipacket reception with successive interference cancelation (SIC) have been shown to improve the performance of multihop wireless networks (MWNs). However, previous work emphasized maximization of network throughput without considering quality of service (QoS) requirements, which may lead to high packet delays in the network. The objective of this work is minimization of packet delay in a TDMA-based MWN that is jointly utilizing NC and SIC techniques for a given traffic demand matrix. We assume conflictfree scheduling and allow multipath routing. We formulate a cross-layer optimization that assigns time slots to links in a way that the average packet delay is minimized. The problem formulation results in a difficult mixed integer nonlinear programming (MINLP) that the state-of-art software can only solve for very small-sized networks. For large networks, we develop a heuristic approach that iteratively determines the optimal solution. We present numerical results, which show that the average packet delay and traffic handling capacity of a network, using w/o NC+SIC, NC, SIC and NC+SIC schemes, improves from left to right. The traffic capacity of NC+SIC is double of the w/o NC+SIC. Thus, combined utilization of NC and SIC techniques results in significant performance improvement.
42	NSZ-04	Distributed denial of service attacks in software-defined networking with cloud computing	IEEE-2015		Although software-defined networking (SDN) brings numerous benefits by decoupling the control plane from the data plane, there is a contradictory relationship between SDN and distributed denial-of-service (DDoS) attacks. On one hand, the capabilities of SDN make it easy to detect and to react to DDoS attacks. On the other hand, the separation of the control plane from the data plane of SDN introduces new attacks. Consequently, SDN itself may be a target of DDoS attacks. In this paper, we first discuss the new trends and characteristics of DDoS attacks in cloud computing environments. We show that SDN brings us a new chance to defeat DDoS attacks in cloud computing environments, and we summarize good features of SDN in defeating DDoS attacks. Then we review the studies about launching DDoS attacks on SDN and the methods against DDoS attacks in SDN.In addition, we discuss a number of challenges that need to be addressed to mitigate DDoS attached in SDN with cloud computing. This work can help understand how to make full use of SDN’s advantages to defeat DDoS attacks in cloud computing environments and how to prevent SDN itself from becoming a victim of DDoSattacks.
43	NSZ-05	Dynamic Openflow-Controlled Optical Packet Switching Network	IEEE-2015		This paper presents and experimentally demonstrates the generalized architecture of Open flow-controlled optical packet switching (OPS) network. Open flow control is enabled by introducing The Openflow/OPS agent into the OPS network, which realizes the Openflow protocol translation and message exchange between the Openflow control plane and the underlying OPS nodes. With software-defined networking (SDN) and Openflow technique, the complex control functions of the conventional OPS network can offloaded into a centralized and flexible control plane, while promoted control and operations can be provided due to centralized coordination of network resources. Furthermore, a contentionaware routing/rerouting strategy as well as a fast network adjustment mechanism is proposed and demonstrated for the first time as advanced Openflow control to route traffic and handle the network dynamics. With centralized SDN/Openflow control, the OPS network has the potential to have better resource utilization and enhanced network resilience at lower cost and less node complexity. Our work will accelerate the development of both OPS and SDN evolution.
44	NSZ-06	Game-Theoretic Topology Controlfor Opportunistic Localizationin Sparse Underwater Sensor Networks	IEEE-2015		In this paper, we propose a localization scheme named Opportunistic Localization by Topology Control (OLTC), specifically for sparse Underwater Sensor Networks (UWSNs). In a UWSN, an unlocalized sensor node finds its location by utilizing the spatio-temporal relation with the reference nodes. Generally, UWSNs are sparsely deployed because of the high implementation cost, and unfortunately, the network topology experiences partitioning due to the effect of passive node mobility. Consequently, most of the underwater sensor nodes lack the required number of reference nodes for localization in underwater environments. The existing literature is deficient in addressing the problem of node localization in the above mentioned scenario. Antagonistically, however, we promote that even in such sparse UWSN context, it is possible to localize the nodes by exploiting their available opportunities.
45	NSZ-07	Improving Physical-Layer Security in Wireless Communications Using Diversity Techniques	IEEE-2015		Due to the broadcast nature of radio propagation, wireless transmission can be readily overheard by unauthorized users for interception purposes and is thus highly vulnerable to eavesdropping attacks. To this end, physical-layer security is emerging as a promising paradigm to protect the wireless communications against eavesdropping attacks by exploiting the physical characteristics of wireless channels. This article is focused on the investigation of diversity techniques to improve physical-layer security differently from the conventional artificial noise generation and beamforming techniques, which typically consume additional power for generating artificial noise and exhibit high implementation complexity for beamformer design. We present several diversity approaches to improve wireless physical-layer security, including multiple-input multiple-output (MIMO), multiuser diversity, and cooperative diversity. To illustrate the security improvement through diversity, we propose a case study
46	NSZ-08	Interference-Based Topology Control Algorithm for Delay-Constrained Mobile Ad Hoc Networks	IEEE-2015		As the foundation of routing, topology control should minimize the interference among nodes, and increase the network capacity. With the development of mobile ad hoc networks (MANETs), there is a growing requirement of quality of service (QoS) in terms of delay. In order to meet the delay requirement, it is important to consider topology control in delay constrained environment, which is contradictory to the objective of minimizing interference. In this paper, we focus on the delay-constrained topology control problem, and take into account delay and interference jointly.
47	NSZ-09	Joint Optimal Data Rate and Power Allocation in Lossy Mobile Ad Hoc Networks with Delay-Constrained Traffics	IEEE-2015		In this paper, we consider lossy mobile ad hoc networks where the data rate of a given flow becomes lower and lower along its routing path. One of the main challenges in lossy mobile ad hoc networks is how to achieve the conflicting goal of increased network utility and reduced power consumption, while without following the instantaneous state of a fading channel. To address this problem, we propose a cross-layer rate-effective network utility maximization (RENUM) framework by taking into account the lossy nature of wireless links and the constraints of rate outage probability and average delay. In the proposed framework, the utility is associated with the effective rate received at the destination node of each flow instead of the injection rate at the source of the flow. We then present a distributed joint transmission rate, link power and average delay control algorithm, in which explicit broadcast message passing is required for power allocation algorithm.
48	NSZ-10	Max Contribution An Online Approximation of Optimal Resource Allocation in Delay Tolerant Networks	IEEE-2015		In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NP-hard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed online approximation algorithm, Distributed Max-Contribution (DMC).
49	NSZ-11	Neighbor Similarity Trust against Sybil Attack in P2P E-Commerce	IEEE-2015		Peer to peer (P2P) e-commerce applications exist at the edge of the Internet with vulnerabilities to passive and active attacks. These attacks have pushed away potential business firms and individuals whose aim is to get the best benefit in e-commerce with minimal losses. The attacks occur during interactions between the trading peers as a transaction takes place. In this paper, we propose how to address Sybil attack, an active attack, in which peers can have bogus and multiple identities to fake their owns. Most existing work, which concentrates on social networks and trusted certification, has not been able to prevent Sybil attack peers from doing transactions. Our work exploits the neighbor similarity trust relationship to address Sybil attack. In our approach, duplicated Sybil attack peers can be identified as the neighbor peers become acquainted and hence more trusted to each other. Security and performance analysis shows that Sybil attack can be minimized by our proposed neighbor similarity trust.
50	NSZ-12	Power Control and Soft Topology Adaptations in Multihop Cellular Networks With Multi-Point Connectivity	IEEE-2015		The LTE standards account for the use of relays to enhance coverage near the cell edge. In a traditional topology, a mobile can either establish a direct link to the base station (BS) or a link to the relay, but not both. In this paper, we consider the benefit of multipoint connectivity in allowing user equipment (UEs) to split their transmit power over simultaneous links to the BS and the relay, in effect transmitting two parallel flows. We model decisions by the UEs as to: (i) which point of access to attach to (either a relay or a relay and the BS or only the BS); and (ii) how to allocate transmit power over these links so as to maximize their total rate. We show that this flexibility in the selection of points of access leads to substantial network capacity increase against when nodes operate in a fixed network topology. Individual adaptations by UEs, in terms of both point of access and transmit power, are interdependent due to interference and to the possibility of over-loading of the backhaul links.
51	NSZ-13	Privacy-Preserving Detection of Privacy-Preserving Detection of Sensitive Data Exposure	IEEE-2015		Statistics from security firms, research institutions and government organizations show that the number of data-leak instances have grown rapidly in recent years. Among various data-leak cases, human mistakes are one of the main causes of data loss. There exist solutions detecting inadvertent sensitive data leaks caused by human mistakes and to provide alerts for organizations. A common approach is to screen content in storage and transmission for exposed sensitive information. Such an approach usually requires the detection operation to be conducted in secrecy. However, this secrecy requirement is challenging to satisfy in practice, as detection servers may be compromised or outsourced. In this paper, we present a privacypreserving data-leak detection (DLD) solution to solve the issue where a special set of sensitive data digests is used in detection. The advantage of our method is that it enables the data owner to safely delegate the detection operation to a semihonest provider without revealing the sensitive data to the provider. We describe how Internet service providers can offer their customers DLD as an add-on service with strong privacy guarantees. The evaluation results show that our method can support accurate detection with very small number of false alarms under various data-leak scenarios.
52	NSZ-14	Security-Aware Relaying Scheme for Cooperative Networks With Untrusted Relay Nodes	IEEE-2015		This paper studies the problem of secure transmission in dual-hop cooperative networks with untrusted relays, where each relay acts as both a potential helper and an eavesdropper. A security-aware relaying scheme is proposed, which employs the alternate jamming and secrecy-enhanced relay selection to prevent the confidential message from being eavesdropped by the untrusted relays. To evaluate the performance of the proposed strategies, we derive the lower bound of the achievable ergodic secrecy rate (ESR), and conduct the asymptotic analysis to examine how the ESR scales as the number of relays increases.
53	NSZ-15	Self-Organizing Resource Management Framework in OFDMA Femtocells	IEEE-2015		Next generation wireless networks (i.e., WiMAX, LTE) provide higher bandwidth and spectrum efficiency leveraging smaller (femto) cells with orthogonal frequency division multiple access (OFDMA). The uncoordinated, dense deployments of femtocells however, pose several unique challenges relating to interference and resource management in OFDMA femtocell networks. Towards addressing these challenges, we propose RADION, a distributed resource management framework that effectively manages interference across femtocells. RADION’s core building blocks enable femtocells to opportunistically determine the available resources in a completely distributed and efficient manner. Further, RADION’s modular nature paves the way for different resource management solutions to be incorporated in the framework. We implement RADION on a real WiMAX femtocell testbed deployed in a typical indoor setting. Two distributed solutions are enabled through RADION and their performance is studied to highlight their quick self-organization into efficient resource allocations.
54	NSZ-16	Statistical Dissemination Control in Large Machine-to-Machine Communication Networks	IEEE-2015		Cloud based machine-to-machine (M2M) communications have emerged to achieve ubiquitous and autonomous data transportation for future daily life in the cyber-physical world. In light of the need of network characterizations, we analyze the connected M2M network in the machine swarm of geometric random graph topology, including degree distribution, network diameter, and average distance (i.e., hops). Without the need of end-to-end information to escape catastrophic complexity, information dissemination appears an effective way in machine swarm. To fully understand practical data transportation, G/G/1 queuing network model is exploited to obtain average end-to-end delay and maximum achievable system throughput. Furthermore, as real applications may require dependable networking performance across the swarm, quality of service (QoS) along with large network diameter creates a new intellectual challenge.
55	NSZ-17	Toward Transparent Coexistence for Multihop Secondary Cognitive Radio Networks	IEEE-2015		The dominate spectrum sharing paradigm of today is interference avoidance, where a secondary network can use the spectrum only when such a use is not interfering with the primary network. However, with the advances of physical-layer technologies, the mindset of this paradigm is being challenged. This paper explores a new paradigm called “transparent coexistence” for spectrum sharing between primary and secondary nodes in a multihop network environment. Under this paradigm, the secondary network is allowed to use the same spectrum simultaneously with the primary network as long as their activities are “transparent” (or “invisible”) to the primary network. Such transparency is accomplished through a systematic interference cancelation (IC) by the secondary nodes without any impact on the primary network. Although such a paradigm has been studied in the information theory (IT) and communications (COMM) communities, it is not well understood in the wireless networking community, particularly for multihop networks.