Iterative merging algorithm for cooperative data exchange

We consider a cooperative data exchange problem with the goal of generating a secret key. Specifically, we investigate the number of public transmissions required for a set of clients to agree on a secret key with probability one, subject to the constraint that it remains private from an eavesdropper. Although the problems are closely related, we prove that secret key generation with fewest linear transmissions is NP-hard, while it is known that the analogous problem in traditional cooperative data exchange can be solved in polynomial time. In doing this, we completely characterize the best-possible performance of linear coding schemes, and also prove that linear codes can be strictly suboptimal.

In this paper, we investigate the use of instantly decodable network coding (IDNC) for improving two fundamental performance metrics, namely, the completion time (as a measure of throughput) and mean decoding delay, in multicast cooperative data exchange (CDE) systems, where a group of geographically close clients cooperate with each other to obtain their missing packets. Here, an IDNC scheme is used for the transmissions across these clients. We utilize the stochastic shortest path (SSP) technique to study the minimum mean completion time problem. However, since finding the optimum solution is intractable, we use the obtained formulation to draw some theoretical guidelines to heuristically find solutions that can efficiently reduce the completion time. Second, we formulate the minimum mean decoding delay problem as selecting the appropriate maximal clique over well-structured graphs at the clients, and in order to reduce its complexity, we propose a simple heuristic algorithm for it. The effectiveness of our proposed algorithms is verified through extensive simulations and comparisons with existing techniques.

We consider the problem of cooperative data exchange in a group of wireless clients. In this problem each client initially holds a subset of packets and needs to obtain all packets held by other clients. Each client can broadcast its own packets or a combinations thereof to other clients via an error-free broadcast channel. Assuming that clients know which packets are available to other clients, our goal is to minimize the total number of transmissions needed to satisfy the demands of all clients. We present a deterministic algorithm that computes an optimal solution to this problem in polynomial time.

Most of Wireless Sensor Networks (WSNs) are usually deployed in hostile environments where the communications conditions are not stable and not reliable. Hence, there is a need to design an effective distributed schemes to enable the sensors cooperating in order to recover the sensed data. In this paper, we establish a novel cooperative data exchange (CDE) scheme using instantly decodable network coding (IDNC) across the sensor nodes. We model the problem using the cooperative game theory in partition form. We develop also a distributed merge-and-split algorithm in order to form dynamically coalitions that maximize their utilities in terms of both energy consumption and IDNC delay experienced by all sensors. Indeed, the proposed algorithm enables these sensors to self-organize into stable clustered network structure where all sensors do not have incentives to change the cluster he is part of. Simulation results show that our cooperative scheme allows nodes not only to reduce the energy consumption, but also the IDNC completion time.

The objective of this project is to evaluate the feasibility of carbon dioxide (CO{sub 2}) sequestration in Texas low-rank coals and to determine the potential for enhanced coalbed methane (CBM) recovery as an added benefit of sequestration. The main objectives for this reporting period were to further characterize the three areas selected as potential test sites, to begin assessing regional attributes of natural coal fractures (cleats), which control coalbed permeability, and to interview laboratories for coal sample testing. An additional objective was to initiate discussions with an operating company that has interests in Texas coalbed gas production and CO{sub 2} sequestration potential, to determine their interest in participation and cost sharing in this project. Well-log data are critical for defining depth, thickness, number, and grouping of coal seams at the proposed sequestration sites. Therefore, we purchased 15 well logs from a commercial source to make coal-occurrence maps and cross sections. Log suites included gamma ray (GR), self potential (SP), resistivity, sonic, and density curves. Other properties of the coals in the selected areas were collected from published literature. To assess cleat properties and describe coal characteristics, we made field trips to a Jackson coal outcrop and visited Wilcox coal exposures at the Sandow surface mine. Coal samples at the Sandow mine were collected for CO{sub 2} and methane sorption analyses. We contacted several laboratories that specialize in analyzing coals and selected a laboratory, submitting the Sandow Wilcox coals for analysis. To address the issue of cost sharing, we had fruitful initial discussions with a petroleum corporation in Houston. We reviewed the objectives and status of this project, discussed data that they have already collected, and explored the potential for cooperative data acquisition and exchange in the future. We are pursuing a cooperative agreement with them.

Textile scientists are seeking for automated ways to understand the wicking phenomenon of blended fabrics from recorded videos at the pixel level. In response to such need, we design a video-based method for detecting pixels that will become wet and for estimating the timestamps of wetting events, which is the first step toward characterizing the wicking phenomenon. Since the wicking behaviors of the blended fabrics can be very different from one yarn to another within a small spatial region, simple frame-level thresholding with morphological preprocessing steps does not fit this application scenario. In this paper, we analyze for each pixel the color variation along the time for the wetting event detection. We develop an iterative merging algorithm rooted from the likelihood ratio test to obtain a coarse-level timestamp. The timestamp is then refined using a parametric curve fitted to a small neighborhood. Experimental results show that our automated method can achieve satisfactory wetting detection performance when the generated binary wetting-event video is compared with the raw wicking video.

This paper presents two new types of transceiver designs for the multi-cell, multi-user, multiple-input-multiple-output (MIMO) interfering broadcast channel (IBC). In contrast to the existing maximum sum rate and max-min fairness transceiver designs, the proposed designs aim at balancing on the two objectives by maximizing the minimum average sum-rate per cell (type-1) or maximizing the minimum average sum-rate within each cell (type-2). Due to the difficulty of these problems, two iterative suboptimal algorithms which ensure local convergence have been proposed. Simulation results show that the proposed algorithms can provide certain level of fairness guarantee without sacrificing much of the overall system performance. As a result, the proposed designs are in some sense more balanced and can be useful alternatives in addition to the existing designs.

Traffic accidents have become an important health and social problem due to the enormous number of fatalities and injuries. The total number of deaths and injuries in the European Union (EU), United States of America (USA) and Japan has been steadily reduced over the last decade. This reduction is mainly attributed to the implementation of a set of road safety measures, such as seat-belt use, vehicle crash protection, traffic-calming interventions and traffic law enforcement. However, the number of accidents has remained uniform due to the increasing number of vehicles and total distance driven (Peden et al., 2004). In addition to passive vehicle safety systems, such as airbags, anti-lock braking system (ABS) and electronic stability control (ESP), new active safety systems have been introduced to improve vehicular safety. To this end, the last decade has witnessed the traffic management industry, engage and promote the integration of information and communications technology (wireless, computing and advanced sensor technologies) into both vehicles and the wider transport infrastructure. These proposals have led to the intelligent transportation system (ITS) concept. At present, different ITS applications have been introduced, such as variable message signs (VMS), located at strategic points (e.g., tunnels and merging highways) or spaced at given distances, to inform drivers about traffic and dangerous situations; automated toll collection systems for highways and parkings; and real-time traffic information broadcasted in the FM radio band. Besides this, onboard ITS applications have improved the assistance and protection mechanisms for drivers: navigation systems, rear and front parking radars, and cameras are extensively used in the vehicle. Vehicles now incorporate sophisticated computing systems, with several sensors interconnected. However, short-range sensors employed in emergency systems, such as forward collision warning and lane keeping assist, are insufficient, specially when these sensors need to extend their communication horizon in emergency cases due to the limitation of their operating range to line-of-sight (LOS) conditions (Vlacic et al., 2001). Therefore, there are safety applications for distance emergency situations, such as blind corners and traffic crossing, where large-range vehicular communication systems are required, e.g., operating rages of about 1000 meters, in both LOS and non-LOS (NLOS) conditions (Gallagher & Akatsuka, 2006). Wireless communications systems which can operate with these constraints are known as cooperative systems on the road. In the cooperative system concept, vehicles and infrastructure exchange safety messages to extend the distance horizon and provide more information in real time to drivers. Cooperative systems involve two

We present DwarfCode, a performance prediction tool for MPI applications on diverse computing platforms. The goal is to accurately predict the running time of applications for task scheduling and job migration. First, DwarfCode collects the execution traces to record the computing and communication events. Then, it merges the traces from different processes into a single trace. After that, DwarfCode identifies and compresses the repeating patterns in the final trace to shrink the size of the events. Finally, a dwarf code is generated to mimic the original program behavior. This smaller running benchmark is replayed in the target platform to predict the performance of the original application. In order to generate such a benchmark, two major challenges are to reduce the time complexity of trace merging and repeat compression algorithms. We propose an O(mpn) trace merging algorithm to combine the traces generated by separate MPI processes, where m denotes the upper bound of tracing distance, p denotes the number of processes, and n denotes the maximum of event numbers of all the traces. More importantly, we put forward a novel repeat compression algorithm, whose time complexity is O(nlogn). Experimental results show that DwarfCode can accurately predict the running time of MPI applications. The error rate is below 10 percent for compute and communication intensive applications. This toolkit has been released for free download as a GNU General Public License v3 software.

Cooperative coherent systems are well-known in radar and countermeasures communities where the transmitter and receiver antennas are co-located on the same platform; hence, the radio frequency (RF) sources are synchronized and the physical separation of coherent systems is limited or confined within the same platform. To improve the effectiveness of cooperative countermeasure systems, it is highly desired to significantly increase the physical separation between cooperative elements. In this paper, we study a non-coherent cooperative RF system where the cooperative elements are located on two separate platforms without hard-line connections to them. Hence, the cooperative signal exchange among multiple cooperative elements has to be transmitted via an RF link and the non-coherent cooperative system would allow the RF source to be located on a separate platform, thus increasing the physical separation. The two cooperative elements are operated with two separate local oscillators, which leads to large non-coherency between multiple platforms.

The wireless body area network (WBAN) is considered as one of the emerging wireless techniques in the healthcare system. Typical WBAN sensors, especially implantable sensors, have limited power capability, which restricts their wide applications in the medical environment. In addition, it is necessary for the healthcare center (HC) to broadcast significant notifications to different patient groups. Considering the above issues, in this paper, the novel practical WBAN system model with group message broadcasting is built. Subsequently, a secure and efficient group key management protocol with cooperative sensor association is proposed. In the proposed protocol, the Chinese remainder theorem (CRT) is employed for group key management between HC and the personal controller (PC), which also supports batch key updating. The proposed sensor association scheme is motivated by coded cooperative data exchange (CCDE). The formal security proofs are presented, indicating that the proposed protocol can achieve the desired security properties. Moreover, performance analysis demonstrates that the proposed protocol is efficient compared with state-of-the-art group key management protocols.

PurposeSecurity of wireless body area network communication is highly important as it directly impacts human life. This paper aims to focus on battlefield application area of WBAN for implementing security where data must be protected against various possible attacks before delivering over a public network.Design/methodology/approachProviding a strong security system is still a research challenge due to low computational power of used sensors for protecting transmission data. In this paper, the authors have proposed an optimized security solution for multithreaded wireless body area network (MWBAN) using trust-based distributed group key management technique to overcome the drawbacks of existing elliptical curve cryptography-homomorphism (ECC-Homomorphism) scheme as well as coded cooperative data exchange group key management (CCDE_GKM) scheme.FindingsThe proposed optimized security solution is implemented for a particular deployment strategy and test runs are conducted. It is found that when number of attack nodes increased to 25, compared to ECC–Homomorphism and CCDE_GKM for the proposed trust-based distributed group key management technique there is an improvement in performance parameters such as throughput is dropped to only 10.11 Kbps, average delay is just 3.4 s, energy consumption is maximum 29 joules, packet loss is only 12.3 per cent, 90.9 per cent truly can detect attack, only 8.9 per cent false attack detection and 84 per cent true negative detection.Social implicationsMedical care can be provided to human beings with much ease and flexibility via remote monitoring. The user can be at any place, can do his/her everyday work while remotely being monitored of their health parameters and secured transmission of their data to the health-care center for medical service in need.Originality/valueThis paper presents an optimized security solution for MWBAN using trust-based distributed group key management technique where bilinear pairing theory is used as major cryptographic base. Optimal key is selected based on trust value and also attack nodes are detected based on trust value to control participation in communication.

Due to the increasing popularity of electric vehicles (EVs) and technological advancements of EV electronics, the vehicle-to-grid (V2G) technique, which utilizes EVs to provide ancillary services for the power grid, stimulates new ideas in current smart grid research. Since EVs are selfish individuals owned by different parties, how to motivate them to provide ancillary services becomes an issue. In this paper, game theoretic approaches using non-cooperative and cooperative game are proposed to motivate EVs to provide frequency regulation services for the power grid. In a non-cooperative V2G system, the interaction between the EV aggregator and EVs is formulated as a non-cooperative Stackelberg game. The EV aggregator as the leader decides the electricity trading price, and EVs as the followers determine their charging/discharging strategies. In a cooperative V2G system, a potential game is formulated to achieve the optimal social welfare of the V2G system. The existence and uniqueness of the Nash equilibrium of these two games are validated. Our simulation results show that the proposed game theoretic approaches can motivate EVs to smooth out the power fluctuations from the grid while EVs schedule their charging/discharging activities to maximize their utilities. This demonstrates the effectiveness of the use of the V2G game in providing regulation services to the grid. Through cooperation and extra information exchange, the social welfare of EVs and the EV aggregator can be improved to the global optimum and the V2G regulation services can also achieve near-optimal performance.

<span>In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced fairness among CR users with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.</span>

Policy sharing between multiple mobile robots using decision trees