Elizabeth S. Bentley

Spread Spectrum Visual Sensor Network Resource Management Using an End-to-End Cross-Layer Design

In this paper, we propose an approach to manage network resources for a direct sequence code division multiple access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer, and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our experimental results demonstrate the effectiveness of the cross-layer optimization.

GAME-theory-based cross-layer optimization for wireless DS-CDMA visual sensor networks

We propose a game-theory-based cross-layer optimization scheme for wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor networks. The scheme uses the Nash Bargaining Solution (NBS), which assumes that the nodes negotiate, with the help of a centralized control unit, on how to allocate resources. The NBS takes into account the video quality each node could achieve without making an agreement. The cross-layer optimization scheme determines the source coding rate, channel coding rate, and transmission power for each node. We compare the proposed game-theory-based scheme with competing schemes that minimize the average or maximum distortion among the nodes. Experimental results are presented and conclusions are drawn.

Heavy-ball: A new approach to tame delay and convergence in wireless network optimization

The last decade has seen significant advances in optimization-based resource allocation and control approaches for wireless networks. However, the existing work suffer from poor performance in one or more of the metrics of optimality, delay, and convergence speed. To overcome these limitations, in this paper, we introduce a largely overlooked but highly effective heavy-ball optimization method. Based on this heavy-ball technique, we develop a cross-layer optimization framework that offers utility-optimality, fast-convergence, and significant delay reduction. Our contributions are three-fold: i) we propose a heavy-ball joint congestion control and routing/scheduling framework for both single-hop and multi-hop wireless networks; ii) we show that the proposed heavy-ball method offers an elegant three-way trade-off in utility, delay, and convergence, which is achieved under a near index-type simple policy; and more importantly, iii) our work opens the door to an unexplored network control and optimization paradigm that leverages advanced optimization techniques based on “memory/momentum” information.

Game-theoretic solutions through intelligent optimization for efficient resource management in wireless visual sensor networks

We propose a quality-driven cross-layer optimization scheme for wireless direct sequence code division multiple access (DS-CDMA) visual sensor networks (VSNs). The scheme takes into account the fact that different nodes image videos with varying amounts of motion and determines the source coding rate, channel coding rate, and power level for each node under constraints on the available bit rate and power. The objective is to maximize the quality of the video received by the centralized control unit (CCU) from each node. However, since increasing the power level of one node will lead to increased interference with the rest of the nodes, simultaneous maximization of the video qualities of all nodes is not possible. In fact, there are an infinite number of Pareto-optimal solutions. Thus, we propose the use of the Nash bargaining solution (NBS), which pinpoints one of the infinite Pareto-optimal solutions, based on the stipulation that the solution should satisfy four fairness axioms. The NBS results in a mixed-integer optimization problem, which is solved using the particle swarm optimization (PSO) algorithm. The presented experimental results demonstrate the advantages of the NBS compared with alternative optimization criteria.

Wireless visual sensor network resource allocation using cross-layer optimization

In this paper, we propose an approach to manage network resources for a Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our approach allows one to determine the capacity of the visual sensor network based on the number of nodes and the quality of video that must be transmitted. For bandwidth-limited applications, one can also determine the minimum bandwidth needed to accommodate a number of nodes with a specific target chip rate. Video captured by a sensor node camera is encoded and decoded using the H.264 video codec by a centralized control unit at the network layer. To reduce the computational complexity of the solution, Universal Rate-Distortion Characteristics (URDCs) are obtained experimentally to relate bit error probabilities to the distortion of corrupted video. Bit error rates are found first by using Viterbis upper bounds on the bit error probability and second, by simulating nodes transmitting data spread by Total Square Correlation (TSC) codes over a Rayleigh-faded DS-CDMA channel and receiving that data using Auxiliary Vector (AV) filtering.

Quality-driven power control and resource allocation in wireless multi-rate Visual Sensor Networks

In the present paper, we deal with the problem of allocating the network resources in multi-rate Direct Sequence Code Division Multiple Access (DS-CDMA) Visual Sensor Networks (VSNs). We consider a single-cell system where each node uses the same chip rate, but can transmit at a different bit rate. In wireless VSNs, we face the constraints of limited power lifetime and of an error-prone environment, mainly due to attenuation and interference. The proposed cross-layer scheme enables the Centralized Control Unit (CCU) to jointly allocate the transmission power, the transmission bit rate and the source-channel coding rates for each VSN node in order to optimize the delivered video quality. The transmission power of each visual sensor assumes values from a continuous range, while the rest of the resources take values chosen from an available discrete set. The numerical results demonstrate the performance of the proposed multi-rate scheme vs a single-rate system.

Diamond-Shaped Mesh Network Routing with Cross-Layer Design to Explore the Benefits of Multi-Beam Smart Antennas

Conventional wireless mesh network (WMN)routing protocols are designed for the nodes that use the omni-directional or single-beam directional antennas. This research presents a throughput-efficient routing scheme for WMN, by taking advantage of the nodes equipped with the multi-beam directional antennas (MBDAs). Our routing design has the following two novel features: First, it is a cross-layer design by integrating the routing scheme with multi-beam oriented medium access control (MAC) scheme. Second, the routing topology has a diamond-like shape and uses the multi-path routes (i.e., one main path and a few side paths). The diamond shape makes the traffic converge and diverge periodically in the routing paths, which exploits the simultaneous data delivery capability of multi-beam antennas, and enhances the network throughput. Our simulation results demonstrate the high throughput efficiency of the proposed multi-beam routing scheme.

Distributed and dynamic spectrum management in airborne networks

Airborne network plays an important role in operations of Air Force. Due to the rapidly-changing topologies, limited wireless communication spectrum, latency, and priorities of tasks, it is vitally important to have dynamic spectrum management between aircrafts and base station in airborne networks. Particularly, we encounter two major challenges: (1) uncertainty about channel quality, in terms of the long-term channel statistics and real-time channel states; (2) the dynamics and the possibly correlated nature of channel quality of different aircrafts. To address these two challenges, we propose a distributed framework for spectrum management in airborne networks, which includes: 1) channel quality prediction based on correlation of channel quality among aircrafts; 2) task scheduling in the aircraft. With real-world trace data, we conduct extensive experiments. Our simulation results show that our design can effectively optimize the channel utilization in airborne network.

Effective Resource Management in Visual Sensor Networks With MPSK

The problem of resource management in a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless Visual Sensor Network (VSN) with M-array Phase Shift Keying (MPSK) modulation in an Additive White Gaussian Network (AWGN) channel was considered in this paper. Achieving maximum video quality, in spite of the prevailing network resource constraints, is of utmost importance in VSN applications. Our optimization scheme is based on the Nash Bargaining Solution (NBS). The nodes in the network negotiate in order to determine their transmission parameters (transmission powers; source and channel coding rates for each node). The task is to optimize the transmission powers (which are continuous) and the source and channel coding rates (which are discrete) for all the network nodes, while taking advantage of the improved bandwidth spectral efficiency provided by the higher order constellation.

Delay Minimization by Adaptive Framing Policy in Cognitive Sensor Networks

In this paper, a delay-minimal joint framing and scheduling policy is proposed for cognitive sensor networks, where a secondary sensor node collects measurement samples, combines them together into packets and transmits the packets to a central data fusion center after proper scheduling, when a shared channel is released by primary nodes. The main objective of this study is to minimize the end-to-end delivery time for secondary sensor nodes based on the current input traffic rate, channel availability process and channel bit error probability. The proposed method outperforms conventional constant-length framing policies for any choice of packet length by minimizing the delay and preventing potential queue instability under dynamic channel conditions. This method can be utilized by secondary nodes in a wide variety of wireless sensing applications in order to collect time-sensitive data with minimal delays