IEEE SIGNAL PROCESSING LETTERS, VOL. 20, NO. 8, AUGUST 2013 739 Effective Resource Management in Visual Sensor Networks With MPSK Olusegun O. Odejide, Elizabeth S. Bentley, Lisimachos P. Kondi, and John D. Matyjas Abstract—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 max- imum 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. Index Terms—Cross layer optimization, game theory, MPSK, Nash bargaining solution, visual sensor network. I. INTRODUCTION T HE reliability of streaming applications over wireless links suffers, as a result of the challenges associated with wireless networks. The output at the application layer can be improved by jointly optimizing parameters at the various layers of the network stack, while considering quality of service (QoS) requirements. This can be achieved by allocating resources (compression ratio at the application layer, channel coding rate at the data link layer, and transmit power at the physical layer) to video camera nodes that negotiate according to the Nash Bargaining Solution (NBS) approach, in order to improve the overall objective video quality of the VSN. Previous research in this field focuses on the important issue of controlling power consumption in VSN [1], [2]. How- ever, solutions presented in [1] did not optimize the overall end-to-end video quality. In other recent work, several ap- proaches have been presented towards achieving an end-to-end video quality by reducing the intra-cell interference with the aid of cross-layer optimization schemes [3]–[5]. However, in previous work only BPSK modulation was considered. Using BPSK limits the bandwidth spectral efficiency (information rate that can be transmitted over a given bandwidth), so a Manuscript received February 21, 2013; revised May 05, 2013; accepted May 16, 2013. Date of publication June 03, 2013; date of current version June 06, 2013. The associate editor coordinating the review of this manuscript and ap- proving it for publication was Prof. Yan Sun. O. O. Odejide, E. S. Bentley, and J. D. Matyjas are with the Air Force Re- search Laboratory, Rome, NY 13441 USA (e-mail: femiodejide@yahoo.com). L. P. Kondi is with the Department of Computer Science, University of Ioan- nina, GR-45110 Ioannina, Greece. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/LSP.2013.2265912 higher spectral efficiency can be obtained by using higher order constellations such as QPSK and 8-PSK. Also in [6], though the authors look at optimizing the cross layer design techniques for video streaming over cooperative wireless networks with distributed control, they did not consider the effect of higher order constellation schemes. Our framework considered spatially distributed nodes, each equipped with a camera capable of recording scenes with high motion and low motion. In order to reduce the effect of interfer- ence and operate optimally within the limits of the network re- source constraints, we need to establish a joint network resource allocation scheme that can enhance the global video quality. In this paper, the cross-layer resource allocation scheme is based on the Nash Bargaining Solution (NBS) from game theory. Resources are allocated by the NBS based on negotia- tions between the nodes, coordinated by the centralized control unit. A Centralized Coordination Unit (CCU) coordinates the resource allocation among the nodes. A multi-user/multi-access channel access method (DS-CDMA) was employed, as well as H.264 AVC video codec. In order to achieve a flexible coding scheme, Rate Compatible Punctured Convolutional Codes (RCPC) were used. Our method ensures fair allocation of resources to obtain satisfactory utilities for all nodes and takes into consideration the various channel conditions, the video content characteristics, and the resource needs of the other nodes so as to achieve the required level of Quality of Service (QoS). The source coding rate and the channel coding rate take on discrete values, whereas the transmission power is allowed to take on values from a continuous set. Hence, the resulting optimization problem is a mixed-integer problem, and it is solved using Particle Swarm Optimization (PSO) [7]. The remainder of the article is organized as follows; in Section II, we discuss the system model and the MPSK mod- ulation scheme using trellis coding. The node clustering and optimization framework is presented briefly in Section III. Se- lected computational results are provided in Section IV which is followed by some concluding remarks in Section V. II. SYSTEM MODEL The focus of this work is the analysis of a multi-node cross- layer optimization technique for resource management in VSNs. This is a cross-layer network performance optimization scheme involving three different layers (physical, data link, and appli- cation): optimization of the transmission powers at the physical layer, optimal channel coding rates at the data link layer, and compression rates at the application layer. Using BPSK mod- ulation and RCPC codes, allowed the channel coding rate to be optimized because variable rates are allowed, however the 1070-9908/$31.00 © 2013 IEEE