DOMAIN: MOBILE COMPUTING
|S. No.||IEEE TITLE||ABSTRACT||IEEE YEAR|
|1.||Cooperative Spectrum Sharing: A Contract-Based Approach||Abstract—Providing economic incentives to all parties involved is essential for the success of dynamic spectrum access. Cooperative spectrum sharing is one effective way to achieve this, where secondary users (SUs) relay traffics for primary users (PUs) in exchange for dedicated spectrum access time for SUs’ own communications. In this paper, we study the cooperative spectrum sharing under incomplete information, where SUs’ wireless characteristics are private information and not known by a PU. We model the PU-SU interaction as a labor market using contract theory. In contract theory, the employer generally does not completely know employees’ private information before the employment and needs to offers employees a contract under incomplete information. In our problem, the PU and SUs are, respectively, the employer and employees, and the contract consists of a set of items representing combinations of spectrum accessing time (i.e., reward) and relaying power (i.e., contribution). We study the optimal contract design for both weakly and strongly incomplete information scenarios. In the weakly incomplete information scenario, we show that the PU will optimally hire the most efficient SUs and the PU achieves the same maximum utility as in the complete information benchmark. In the strongly incomplete information scenario, however, the PU may conservatively hire less efficient SUs as well. We further propose a decompose-and-compare (DC) approximate algorithm that achieves a close-to-optimal contract. We further show that the PU’s average utility loss due to the suboptimal DC algorithm and the strongly incomplete information are relatively small (less than 2 and 1.3 percent, respectively, in our numerical results with two SU types).||2014|
|2.||Energy-Aware Resource Allocation Strategies for LTE Uplink with Synchronous HARQ Constraints||Abstract—In this paper, we propose a framework for energy efficient resource allocation in multiuser localized SC-FDMA with synchronous HARQ constraints. Resource allocation is formulated as a two-stage problem where resources are allocated in both time and frequency. The impact of retransmissions on the time-frequency problem segmentation is handled through the use of a novel block scheduling interval specifically designed for synchronous HARQ to ensure uplink users do not experience ARQ blocking. Using this framework, we formulate the optimal margin adaptive allocation problem, and based on its structure, we propose two suboptimal approaches to minimize average power allocation required for resource allocation while attempting to reduce complexity. Results are presented for computational complexity and average power allocation relative to system complexity and data rate, and comparisons are made between the proposed optimal and suboptimal approaches.||2014|
|3.||Preserving Location Privacy in Geosocial Applications||Abstract—Using geosocial applications, such as FourSquare, millions of people interact with their surroundings through their friends and their recommendations. Without adequate privacy protection, however, these systems can be easily misused, for example, to track users or target them for home invasion. In this paper, we introduce LocX, a novel alternative that provides significantly improved location privacy without adding uncertainty into query results or relying on strong assumptions about server security. Our key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. The friends of a user share this user’s secrets so they can apply the same transformation. This allows all location queries to be evaluated correctly by the server, but our privacy mechanisms guarantee that servers are unable to see or infer the actual location data from the transformed data or from the data access. We show that LocX provides privacy even against a powerful adversary model, and we use prototype measurements to show that it provides privacy with very little performance overhead, making it suitable for today’s mobile devices.||2014|
|5.||Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks||Abstract—Data collection is a common operation of Wireless Sensor Networks (WSNs), of which the performance can be measured by its achievable network capacity. Most existing works studying the network capacity issue are based on the unpractical model called deterministic network model. In this paper, a more reasonable model, probabilistic network model, is considered. For snapshot data collection, we propose a novel Cell-based Path Scheduling (CPS) algorithm that achieves capacity of Ω (1/5ѡ ln n. W) in the sense of the worst case and order-optimal capacity in the sense of expectation, where n is the number of sensor nodes, ѡ is a constant, and W is the data transmitting rate. For continuous data collection, we propose a Zone-based Pipeline Scheduling (ZPS) algorithm. ZPS significantly speeds up the continuous data collection process by forming a data transmission pipeline, and achieves a capacity gain of N times better than the optimal capacity of the snapshot data collection scenario in order in the sense of the worst case, where N is the number of snapshots in a continuous data collection task. The simulation results also validate that the proposed algorithms significantly improve network capacity compared with the existing works.||2014|
|6.||A QoS-Oriented Distributed Routing Protocol for Hybrid Wireless Networks||Abstract—As wireless communication gains popularity, significant research has been devoted to supporting real-time transmission with stringent Quality of Service (QoS) requirements for wireless applications. At the same time, a wireless hybrid network that integrates a mobile wireless ad hoc network (MANET) and a wireless infrastructure network has been proven to be a better alternative for the next generation wireless networks. By directly adopting resource reservation-based QoS routing for MANETs, hybrids networks inherit invalid reservation and race condition problems in MANETs. How to guarantee the QoS in hybrid networks remains an open problem. In this paper, we propose a QoS-Oriented Distributed routing protocol (QOD) to enhance the QoS support capability of hybrid networks. Taking advantage of fewer transmission hops and anycast transmission features of the hybrid networks, QOD transforms the packet routing problem to a resource scheduling problem. QOD incorporates five algorithms: 1) a QoS-guaranteed neighbor selection algorithm to meet the transmission delay requirement, 2) a distributed packet scheduling algorithm to further reduce transmission delay, 3) a mobility-based segment resizing algorithm that adaptively adjusts segment size according to node mobility in order to reduce transmission time, 4) a traffic redundant elimination algorithm to increase the transmission throughput, and 5) a data redundancy elimination-based transmission algorithm to eliminate the redundant data to further improve the transmission QoS. Analytical and simulation results based on the random way-point model and the real human mobility model show that QOD can provide high QoS performance in terms of overhead, transmission delay, mobility-resilience, and scalability.||2014|
|7.||Cooperative Caching for Efficient Data Access in Disruption Tolerant Networks||Abstract—Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. In this paper, we propose a novel approach to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduces data access delay. Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We propose an efficient scheme that ensures appropriate NCL selection based on a probabilistic selection metric and coordinates multiple caching nodes to optimize the tradeoff between data accessibility and caching overhead. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes.||2014|
|8.||Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach||Abstract—The distributed nature of the CSMA/CA-based wireless protocols, for example, the IEEE 802.11 distributed coordinated function (DCF), allows malicious nodes to deliberately manipulate their backoff parameters and, thus, unfairly gain a large share of the network throughput. In this paper, we first design a real-time backoff misbehavior detector, termed as the fair share detector (FS detector), which exploits the nonparametric cumulative sum (CUSUM) test to quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior. While most of the existing schemes for selfish misbehavior detection depend on heuristic parameter configuration and experimental performance evaluation, we develop a Markov chain-based analytical model to systematically study the performance of the FS detector in real-time backoff misbehavior detection. Based on the analytical model, we can quantitatively compute the system configuration parameters for guaranteed performance in terms of average false positive rate, average detection delay, and missed detection ratio under a detection delay constraint. We present thorough simulation results to confirm the accuracy of our theoretical analysis as well as demonstrate the performance of the developed FS detector.||2014|
|9.||A Neighbor Coverage-Based Probabilistic Rebroadcast for Reducing Routing Overhead in Mobile Ad Hoc Networks||Due to high mobility of nodes in mobile ad hoc networks (MANETs), there exist frequent link breakages which lead to frequent path failures and route discoveries. The overhead of a route discovery cannot be neglected. In a route discovery, broadcasting is a fundamental and effective data dissemination mechanism, where a mobile node blindly rebroadcasts the first received route request packets unless it has a route to the destination, and thus it causes the broadcast storm problem. In this paper, we propose a neighbor coverage-based probabilistic rebroadcast protocol for reducing routing overhead in MANETs. In order to effectively exploit the neighbor coverage knowledge, we propose a novel rebroadcast delay to determine the rebroadcast order, and then we can obtain the more accurate additional coverage ratio by sensing neighbor coverage knowledge. We also define a connectivity factor to provide the node density adaptation. By combining the additional coverage ratio and connectivity factor, we set a reasonable rebroadcast probability. Our approach combines the advantages of the neighbor coverage knowledge and the probabilistic mechanism, which can significantly decrease the number of retransmissions so as to reduce the routing overhead, and can also improve the routing performance.||2013|
|10.||Relay Selection for Geographical Forwarding in Sleep-Wake Cycling Wireless Sensor Networks
|Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. We seek to develop local forwarding algorithms that can be tuned so as to tradeoff the end-to-end delay against a total cost, such as the hop count or total energy. Our approach is to solve, at each forwarding node enroute to the sink, the local forwarding problem of minimizing one-hop waiting delay subject to a lower bound constraint on a suitable reward offered by the next-hop relay; the constraint serves to tune the tradeoff. The reward metric used for the local problem is based on the end-to-end total cost objective (for instance, when the total cost is hop count, we choose to use the progress toward sink made by a relay as the reward). The forwarding node, to begin with, is uncertain about the number of relays, their wake-up times, and the reward values, but knows the probability distributions of these quantities. At each relay wake-up instant, when a relay reveals its reward value, the forwarding node’s problem is to forward the packet or to wait for further relays to wake-up. In terms of the operations research literature, our work can be considered as a variant of the asset selling problem. We formulate our local forwarding problem as a partially observable Markov decision process (POMDP) and obtain inner and outer bounds for the optimal policy. Motivated by the computational complexity involved in the policies derived out of these bounds, we formulate an alternate simplified model, the optimal policy for which is a simple threshold rule. We provide simulation results to compare the performance of the inner and outer bound policies against the simple policy, and also against the optimal policy when the source knows the exact number of relays. Observing the good performance and the ease of implementation of the simple policy, we apply it to our motivating problem, i.e., local geographical routing of sporadic alarm packets in a large WSN. We compare the end-to-end performance (i.e., average total delay and average total cost) obtained by the simple policy, when used for local geographical forwarding, against that obtained by the globally optimal forwarding algorithm proposed by Kim et al.||2013|
|11.||Toward a Statistical Frame work for Source Anonymity in Sensor Networks
|In certain applications, the locations of events reported by a sensor network need to remain anonymous. That is, unauthorized observers must be unable to detect the origin of such events by analyzing the network traffic. Known as the source anonymity problem, this problem has emerged as an important topic in the security of wireless sensor networks, with variety of techniques based on different adversarial assumptions being proposed. In this work, we present a new framework for modeling, analyzing, and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of interval indistinguishability” and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem of
binary hypothesis testing with nuisance parameters. We then analyze existing solutions for designing anonymous sensor networks using the proposed model. We show how mapping source anonymity to binary hypothesis testing with nuisance parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information. By doing so, we transform the problem from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. Finally, we discuss how existing solutions can be modified to improve their anonymity.
|12.||Cell Selection in 4G Cellular Networks||Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step toward maximizing the utilization of current and future cellular networks. We study the potential benefit of global cell selection versus the current local mobile SNR-based decision protocol. In particular, we study the new possibility available
in OFDMA-based systems, such as IEEE 802.16m and LTE-Advanced, of satisfying the minimal demand of a mobile station simultaneously by more than one base station. We formalize the problem as an optimization problem, and show that in the general case this problem is not only NP-hard but also cannot be approximated within any reasonable factor. In contrast, under the very practical assumption that the maximum required bandwidth of a single mobile station is at most an r-fraction of the capacity of a base
station, we present two different algorithms for cell selection. The first algorithm produces a approximate solution, where a mobile station can be covered simultaneously by more than one base station. The second algorithm produces a approximate solution, while every mobile station is covered by at most one base station. We complete our study by an extensive simulation study demonstrating the benefits of using our algorithms in high-loaded capacity-constrained future 4G networks, compared to currently used methods. Specifically, our algorithms obtain up to 20 percent better usage of the network’s capacity, in comparison with the current cell selection algorithms.
|13.||Distributed Cooperation and Diversity for Hybrid Wireless Networks||In this paper, we propose a new Distributed Cooperation and Diversity Combining framework. Our focus is on heterogeneous networks with devices equipped with two types of radio frequency (RF) interfaces: short-range high-rate interface (e.g.,
IEEE802.11), and a long-range low-rate interface (e.g., cellular) communicating over urban Rayleigh fading channels. Within this framework, we propose and evaluate a set of distributed cooperation techniques operating at different hierarchical levels with resource
constraints such as short-range RF bandwidth. We propose a Priority Maximum-Ratio Combining (PMRC) technique, and a Post Soft- Demodulation Combining (PSDC) technique. We show that the proposed techniques achieve significant improvements on Signal to Noise Ratio (SNR), Bit Error Rate (BER) and throughput through analysis, simulation, and experimentation on our software radio testbed. Our results also indicate that, under several communication scenarios, PMRC and PSDC can improve the throughput performance by over an order of magnitude.
|13.||Privacy-Preserving Distributed Profile Matching in Proximity-Based Mobile Social Networks||Making new connections according to personal preferences is a crucial service in mobile social networking, where an initiating user can find matching users within physical proximity of him/her. In existing systems for such services, usually all the users directly publish their complete profiles for others to search. However, in many applications, the users’ personal profiles may contain sensitive information that they do not want to make public. In this paper, we propose FindU, a set of privacy-preserving profile matching schemes for proximity-based mobile social networks. In FindU, an initiating user can find from a group of users the one whose profile best matches with his/her; to limit the risk of privacy exposure, only necessary and minimal information about the private attributes of the participating users is exchanged. Two increasing levels of user privacy are defined, with decreasing amounts of revealed profile information. Leveraging secure multi-party computation (SMC) techniques, we propose novel protocols that realize each of the user privacy levels, which can also be personalized by the users. We provide formal security proofs and performance evaluation on our schemes, and show their advantages in both security and efficiency over state-of-the-art schemes.||2013|