Design and performance analysis of a zonal DCT-based image encoder for Wireless Camera Sensor Networks

Tiny block-size coding for energy-efficient image compression and communication in wireless camera sensor networks

Entropy encoder for low-power low-resources high-quality CFA image compression

The Multi-Wireless-Agent-Communication (MWAC) model uses a multiagent self-organization process through to manage communications in wireless sensor networks. This paper presents a first improvement of the MWAC model using an ant colony optimization. We introduce the use of ant colony optimization in the context of multiagent systems and wireless sensor networks. Ants are not simply deployed on the multiagent society. Each ant interacts with agents to obtain the best compromise on the routes choice to enable a reliable communication.

In this paper, we examine some of the challenges concerning error correction and multi-hop communication in wireless sensor networks (WSNs). We consider Bose, Chaudhuri and Hoquenghem (BCH) codes with different codeword lengths and error correction capabilities. In contrast with previous works, that implement coding algorithm in hardware and consequently used hardware energy profiling, in this work we consider a more realistic assumption that the node's /spl mu/-processor performs coding and energy consumption of decoding is measured using JouleTrack. Energy efficiency is used as the performance metric for communication and the interaction of multi-hop communication and coding is investigated. Simulation results show that communicating long packets is more energy efficient. If communication is multi-hop with sufficient number of hops, then, the uncoded system is beneficial. However, coding is inevitable in the case where intermediate nodes, when needed, are not available.

The quality of wireless communication makes a great impact on the performance of wireless sensor networks, but wireless communication has the notorious reputation of being unpredictable. The paper discusses reliable communication in wireless sensor networks at the data link layer. We provide reliable many-to-one and point-to-point communication ability by dynamically adjusting the power settings of the radio transceivers. Our results might be helpful for those who are puzzled by the packet loss problem in wireless sensor networks.

There is a plethora of recent research on high performance wireless communications using a cross‐layer approach in that adaptive modulation and coding (AMC) schemes at wireless physical layer are used for combating time varying channel fading and enhance link throughput. However, in a wireless sensor network, transmitting packets over deep fading channel can incur excessive energy consumption due to the usage of stronger forwarding error code (FEC) or more robust modulation mode. To avoid such energy inefficient transmission, a straightforward approach is to temporarily buffer packets when the channel is in deep fading, until the channel quality recovers. Unfortunately, packet buffering may lead to communication latency and buffer overflow, which, in turn, can result in severe degradation in communication performance. Specifically, to improve the buffering approach, we need to address two challenging issues: (1) how long should we buffer the packets? and (2) how to choose the optimum channel transmission threshold above which to transmit the buffered packets? In this paper, by using discrete‐time queuing model, we analyze the effects of Rayleigh fading over AMC‐based communications in a wireless sensor network. We then analytically derive the packet delivery rate and average delay. Guided by these numerical results, we can determine the most energy‐efficient operation modes under different transmission environments. Extensive simulation results have validated the analytical results, and indicates that under these modes, we can achieve as much as 40% reduction in energy dissipation. Copyright © 2008 John Wiley & Sons, Ltd.

This paper deals with image compression over Wireless Camera Sensor Networks (WCSNs) in order to decrease the energy consumption of sensors and thus to maintain a long network lifetime. As the radio tranceiver is the most power greedy components of sensor nodes, it seems natural to consider lossy compression before transmission as the appropriate answer to the problem of energy consumption. However, the limitation of sensor nodes in terms of memory as well as processor speed makes most of the compression algorithms inapplicable. Indeed, the most popular methods such as JPEG or JPEG2000 can yield a higher energy consumption than when transmitting uncompressed images. Here we propose to solve this problem by the design of a fast zonal DCT-based image compression algorithm which allows an efficient tuning of the trade-off between energy consumption and image distortion, as shown by experimental results provided in the paper.

Due to the constraints of wireless communications in general and wireless sensor networks in particular, the layered model is poor in mechanisms to support QoS (Quality of service) in such networks. However, the cross-layer model proposes different techniques and architectures allowing collaboration between layers to overcome the limitations of the layered model. In this context, we have proposed the HCQ (Hierarchical Cross-layer approach for QoS provisioning in WSN) model which uses a cross-layer architecture allowing the support of QoS in a monitoring application with different types of traffic. Indeed, our contribution involves three layers, namely, the application layer, the network layer, and the MAC (Medium Access Control) layer. Synchronization between the three layers is implemented allowing the same interpretation of the assigned priorities.

Understanding Packet Delivery Performance In Dense Wireless Sensor Networks ∗ Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Jerry Zhao Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Ramesh Govindan zhaoy@usc.edu ABSTRACT Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environ- ments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspec- tive, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal charac- teristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. ramesh@usc.edu spectrum under use, the particular modulation schemes un- der use, and possibly on the communicating devices them- selves. Communication quality can vary dramatically over time, and has been reputed to change with slight spatial displacements. All of these are true to a greater degree for ad-hoc (or infrastructure-less) communication than for wire- less communication to a base station. Given this, and the paucity of large-scale deployments, it is perhaps not surpris- ing that there have been no medium to large-scale measure- ments of ad-hoc wireless systems; one expects measurement studies to reveal high variability in performance, and one suspects that such studies will be non-representative. Wireless sensor networks [5, 7] are predicted on ad-hoc wireless communications. Perhaps more than other ad-hoc wireless systems, these networks can expect highly variable wireless communication. They will be deployed in harsh, inaccessible, environments which, almost by definition will exhibit significant multi-path communication. Many of the current sensor platforms use low-power radios which do not have enough frequency diversity to reject multi-path prop- agation. Finally, these networks will be fairly densely de- ployed (on the order of tens of nodes within communica- tion range). Given the potential impact of these networks, and despite the anecdotal evidence of variability in wireless communication, we argue that it is imperative that we get a quantitative understanding of wireless communication in sensor networks, however imperfect. Our paper is a first attempt at this. Using up to 60 Mica motes, we systematically evaluate the most basic aspect of wireless communication in a sensor network: packet delivery. Particularly for energy-constrained networks, packet de- livery performance is important, since that translates to net- work lifetime. Sensor networks are predicated using low- power RF transceivers in a multi-hop fashion. Multiple short hops can be more energy-efficient than one single hop over a long range link. Poor cumulative packet delivery per- formance across multiple hops may degrade performance of data transport and expend significant energy. Depending on the kind of application, it might significantly undermine application-level performance. Finally, understanding the dynamic range of packet delivery performance (and the ex- tent, and time-varying nature of this performance) is impor- tant for evaluating almost all sensor network communication protocols. We study packet delivery performance at two layers of the communication stack (Section 3). At the physical-layer and in the absence of interfering transmissions, packet de- Categories and Subject Descriptors C.2.1 [Network Architecture and Design]: Wireless communication; C.4 [Performance of Systems]: Perfor- mance attributes, Measurement techniques General Terms Measurement, Experimentation Keywords Low power radio, Packet loss, Performance measurement 1. INTRODUCTION Wireless communication has the reputation of being no- toriously unpredictable. The quality of wireless communica- tion depends on the environment, the part of the frequency ∗ This work is supported in part by NSF grant CCR-0121778 for the Center for Embedded Systems. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SenSys’03, November 5–7, 2003, Los Angeles, California, USA. Copyright 2003 ACM 1-58113-707-9/03/0011 ... $ 5.00.

Aimed at the problem of unbalanced energy consumption of cluster heads caused by inter-cluster communications in wireless sensor networks clustering routing protocols, a novel algorithm named cluster head load balanced clustering (CHLBC) is presented. Based on uneven distributed cluster heads, CHLBC builds backbone network's inter-cluster transit route which is composed of cluster heads and calculates relay traffic of cluster heads. Sensors take the cluster head's relay traffic into consideration in the process of choosing the best cluster head and realize load balance of cluster heads. Simulation results show that the routing protocol effectively balances the load among cluster heads and achieves an obvious improvement on the network lifetime.

This paper presents the distributed transport for sensor networks (DTSN), a novel reliable transport protocol for convergecast and unicast communications in wireless sensor networks (WSNs). In DTSN, the source completely controls the loss recovery process in order to minimize the overhead associated with control and data packets. The basic loss recovery algorithm is based on selective repeat ARQ, employing both positive and negative acknowledgements. DTSN is able to detect when all packets of a session are lost, besides scattered gaps in the packet sequence. Caching at intermediate nodes is used to avoid the inefficiency of the strictly end-to-end transport reliability TCP-like model, commonly employed in broadband networks. Reliability differentiation is achieved by means of the smart integration of partial buffering at the source, integrated with erasure coding and caching at intermediate nodes. The simulation results attest the effectiveness of both the full reliability and the reliability differentiation mechanisms in DTSN.

Recent advancement in ubiquitous healthcare evolves to new challenges in ubiquitous communications. Secure communication in wireless sensor networks (WSNs) is one of the important issues, especially, when WSN comes to ubiquitous healthcare, where security is main requirement in sensor devices, communication and continuous real-time monitoring of patient in hospital or home network. WSN requires efficient and automated secure communication between distributed applications running upon them. Existing middleware approaches to secure communication cannot satisfy the advanced requirement in wireless sensor network. In this paper we proposed a secure progressive middleware which certainly enhance the quality of data transfer, provides secure communication and also improve the quality of service with several modules. This middleware composed on different medical sensors (tri-axial accelerometer, ECG and temperature) and healthcare application module In addition, to protect critical sensor data from unauthorized access has been considered one of the basic goal of this middleware which is achieved by implementing a PingPong-128 stream cipher algorithm in data communication from sensor devices to application modules. With this prototype a secure middleware is presented and implemented in this paper with several other measurements such as performance, portability, scalability and security.

Wireless sensor nodes generally have less memory and low battery life. Due to this constraint, a strong algorithm is needed which can reduce the energy consumption. Communication in wireless sensor network (WSN) depends on active number of neighboring nodes and battery power of the operating node. Factors like neighbor availability, link stability, energy and route failures directly influence network performance, for which optimization is vital. Traditional optimization techniques advise solutions that consume higher number of iterations without considering post network metrics like link stability and path cost. To address the issues of the existing energy optimization techniques, we put forward an innovative distance and energy aware optimized routing (DEA-OR) algorithm for WSNs. Considering distance as the base factor, DEA-OR algorithm gives solution for energy efficient transmission and route failure recovery. The process is of two stages: weight based neighbor selection for routing and cost-confined greedy method for route failure recovery. In this process, backtracking process of source is prevented through which overhead in neighbor selection is minimized. Our proposed algorithm minimizes energy consumption, delay and overhead thereby improvising throughput and network lifetime.

Designing a group key management scheme for group communication in wireless sensor network is a challenging task given the limited energy, computational power and memory of the sensor nodes. A group key management scheme should satisfy backward secrecy and forward secrecy security requirements in case of sensor revocation and new sensor join respectively. All the existing schemes are analyzed for their security under passive attack model. However, active outsider adversary model in which as adversary is allowed to compromise the legitimate sensor of the group is a strong model. In this work, we show that the key management schemes for wireless sensor networks based on bivariate polynomials, exclusive basis systems, key tree etc are not secure against active outsider model. In particular, we show that an outside adversary by compromising the legitimate sensor could obtain access not only to the current session group key but also the past group keys. Adversary can get the past keys despite the fact that the sensor nodes have erased the past group keys. To secure them against active adversary all the keys should be updated for every rekeying event which incurs additional cost of computation and communication for managing keys. We also give the methods to secure the schemes under active outsider adversary model.

Event detection concerns identifying occurrence of interesting events which are meaningful and understandable. In dynamic fields, as time passes the attribute of phenomenon varies in spatial locations. Detecting events in dynamic fields requires an approach to deal with the highly granular data arriving in real time. This paper proposes a spatiotemporal event detection algorithm in dynamic fields which are monitored by wireless sensor networks (WSNs). The algorithm provides a method using probabilistic graphical models (PGMs) in WSNs to cope with the uncertainty of sensor readings. The algorithm incorporates the ability of Markov chains in temporal dependency modelling and Markov random fields theory to model the spatial dependency of sensors in a distributed fashion. Experimental evaluation of the proposed algorithm demonstrates that the decentralized approach improves the F1-score to 82% and 29% better precision than simple threshold technique. In addition, the performance of the algorithm was evaluated and compared with respect to the scalability (in terms of communication complexity). In comparison with the centralized approach the decentralized algorithm can substantially improve the scalability of communication in wireless sensor networks.