ABSTRACTRelay selection schemes for cooperative communications to achieve full cooperative diversity gains while maintaining spectral and energy efficiency have been extensively studied in a recent research. These schemes select only the best relay from multiple relaying candidates to cooperate with a communication link. In the present paper, we reviewed recently proposed cooperative communication protocols that integrate with relay selection mechanisms. The key design issues for relay selection mechanisms, for example, relaying candidate selection, optimal relay assignment, and cooperative transmission, were identified. We further discussed the challenges of optimal relay assignment in multi‐hop wireless sensor networks and presented the potential applications of cooperative communications with a relay selection in such networks. Future research directions were outlined, for example, the issues of service differentiation and system fairness in cooperative communication systems and the joint use of game theory and adaptive learning techniques in relaying candidate selection and optimal‐relay assignment mechanisms for efficient allocation of network resources. Copyright © 2011 John Wiley & Sons, Ltd.

Context-awareness assists ubiquitous media applications in discovering the changeable contextual information and adapting their behaviors accordingly. A wide spectrum of context-aware schemes have been proposed over the last decade. However, most of them provide partial functionalities of context-awareness in ubiquitous media applications. They are specified to a certain task and lack of systematic research on context-awareness. To this end, this survey aims at answering how close we are to developing context-aware applications in ubiquitous media in a systematic manner. This survey proposes a reference framework to identify key functionalities of context-awareness. Then, it investigates the state-of-the-art advances in every functionality of context-awareness. Finally, it points out potential directions in context-awareness research and tools for building and measuring context-aware ubiquitous media systems.

Body area network (BAN) technology has emerged in recent years as a subcategory of wireless sensor network technology targeted at monitoring physiological and ambient conditions surrounding human beings and animals. However, BAN technology also introduces a number of challenges seldom seen before due to the scarcity of hardware and radio communication resources and the special properties of the radio environment under which they operate. In this chapter, we review the foundations of BANs along with the most relevant aspects relating to their design and deployment. We introduce current, state-of-the-art applications of BAN, as well as the most challenging aspects concerning their adoption and gradual deployment. We also discuss issues pertaining to sensor node communications, trade-offs, and interfacing with external infrastructure, in addition to important aspects relating to wearable sensor technology, enabling software and hardware, as well as future trends and open research issues in BANs.

The design, development and deployment of Mobile Agent (MA) systems for high-level inference and surveillance in wireless sensor networks and RFID systems have drawn increasing attention in the past decade. To answer how the state-of-the-art of MA in a wide range of ubiquitous and sensor environments is, this paper investigates the current progress of MA. It proposes a taxonomy, by which MA systems in ubiquitous computing environments are decomposed and discussed. Then, this paper provides insights into the strengths and weaknesses of existing efforts. Finally, it presents a series of solutions from the viewpoint of various roles of MA in ubiquitous environments and situations.

Low power consumption and high data rate are the most important requirements for the communication system. Especially, very low power consumption modulation method is required for the short range communication systems such as the medical implantable communication devices or capsule endoscope, and so on. For the higher data rate, we like to combine the OFDM system into the QAPM since the OFDM system has higher bandwidth efficiency than a single-carrier system. In this paper, we like to propose a QAPM (Quadrature amplitude position modulation) method combined with the orthogonal frequency-division multiplexing (OFDM) system. Next, we analyze the performance of three low-power-consumption modulation schemes: the phase shift position modulation (PSPM), phase silence shift keying (PSSK), and QAPM using orthogonal frequency-division multiplexing (OFDM) system in the multi-path channel. These schemes have lower bandwidth efficiency and the higher power efficiency than the existing phase-shift keying (PSK) and quadrature amplitude modulation (QAM) schemes. It can be shown that they can achieve greater power efficiency because every modulation symbol has a zero-envelope period as in pulse-position modulation (PPM) techniques. Finally, we compare the performances of the PSPM, PSSK, and QAPM modulation combined with the OFDM system with regard to bit error rate performance and throughput.

As a new multimedia information acquisition and processing method, wireless multimedia sensor network (WMSN) has great application potential and attracts more and more attentions. Compared to traditional wireless sensor networks, the routing design of WMSN has higher requirements on the quality of service (QoS). This paper systemically analyzes the similarity between social network and WMSN, then designs a QoS trust estimation model based on social network analysis, which enables each sensor node measuring the service quality by monitoring the behaviors of neighbor nodes. An energy efficient QoS assurance routing based on cluster hierarchy (EEQAR) is proposed to achieve energy efficiency and meet the requirement of QoS. To obtain a better performance, EEQAR routing adopts cellular topology to form the cluster structure and balance the energy consumption by structure movement. The simulation results show the high performance of EEQAR routing in lifetime and quality of service.

To achieve full cooperative diversity gains while still maintaining spectral and energy efficiency, relay assignment schemes for cooperative communications have been extensively studied in recent research. These schemes select only the best relay from multiple relaying candidates to cooperate with a communication link. In this paper, we formulate the problem of relay assignment as a non-cooperative, mixed strategy, repeated game, where relaying candidates are modeled as rational players. We then propose a Game Theory based Relay Assignment scheme GTRA, in which each player plays against all the other players, and determines whether to cooperate with a communication link on a packet-by-packet basis in a distributed manner. To adapt to dynamic environments, an adaptive learning algorithm is utilized by players to learn optimal strategies of relay assignment, as well as orienting the game to converge to a set of correlated equilibriums. We compare GTRA with BR, a fictitious game based approach. The simulation results show that GTRA outperforms BR in terms of network throughput, especially in environments where the channel fading becomes severe. It is also shown that GTRA can converge to a correlated equilibrium in a short period that enables it to work well in dynamic environments.

This paper is an extended version of the Credo Methodology [16]. Credo offers tools and techniques to model and analyze highly reconfigurable distributed systems. In a previous version we presented an integrated methodology to use the Credo tool suite. Following a compositional, component–based approach to model and analyze distributed systems, we presented a separation of the system into components and the network. A high–level, abstract representation of the dataflow level on the network was given in terms of behavioral interface automata and a detailed model of the components in terms of Creol models. Here we extend the methodology with a detailed model of the network connecting these components. The Vereofy tool set is used to model and analyze the dataflow of the network in detail. The behavioral automata connect the detailed model of the network and the detailed model of the components. We apply the extended methodology to our running example, a peer-to-peer file-sharing system.

A Wireless Body Area Sensor Network (WBASN) is a radio-frequency (RF) based wireless networking technology that interconnects tiny nodes with sensor or actuator capabilities in, on or around a human body. Complementing the coverage of Wireless Personal Area Networks (WPANs), WBASNs target diverse applications. This paper extensively evaluates the performance of ZigBee technology for WBASN-WPAN system by analysis and computer simulations. Specifically, we configure the system deployment, network structure, applicable data rates for WBASN sensor nodes, and underlying radio parameters. Average reception ratio, throughput and latency have been evaluated for the overall system performance; fairness across sensor nodes has been examined; preliminary results regarding mobility support of ZigBee for WBASN are also shown. After examining the performance of ZigBee network with our WBASN-WPAN configurations, we come to the conclusion that serveral optimizations should be done before applying ZigBee to such a system.

To achieve full cooperative diversity gains while still obtaining spectral and energy efficiency, cooperative communications with relay selection schemes, i.e., only the best relay is selected from multiple relaying candidates to cooperate with the communication, have been extensively studied in recent research. In this paper, we review the recent research on optimal relay assignment for cooperative communications, and investigate the use of cooperative communications with adaptive relay selection for soft QoS provisioning in resource-constrained wireless sensor networks. We propose EEARS, an energy-efficient adaptive relay selection scheme, which is based on a multi-agent reinforcement learning framework. In EEARS, optimal relays, in terms of outage probability, spectral and energy efficiency, are selected distributedly from multiple relaying candidates to participate in the communication, without the needs of prior knowledge of the wireless network model and centralized control. Simulation results show that EEARS fits well in dynamic environments, and is effective in improving the satisfying level of soft QoS provisioning for WSNs, i.e., increasing the spectral and energy efficiency, and reducing the amount of time that QoS violation occurs, by exploiting spatial and time diversities. Furthermore, compared with schemes using fixed transmitting power, EEARS can achieve a higher energy efficiency by varying the transmission power level according to wireless channel conditions.

This paper is an extended version of the Credo Methodology [16]. Credo offers tools and techniques to model and analyze highly reconfigurable distributed systems. In a previous version we presented an integrated methodology to use the Credo tool suite. Following a compositional, component based approach to model and analyze distributed systems, we presented a separation of the system into components and the network. A high level, abstract representation of the dataflow level on the network was given in terms of behavioral interface automata and a detailed model of the components in terms of Creol models. Here we extend the methodology with a detailed model of the network connecting these components. The Vereofy tool set is used to model and analyze the dataflow of the network in detail. The behavioral automata connect the detailed model of the network and the detailed model of the components. We apply the extended methodology to our running example, a peer-to-peer file-sharing system.

Credo offers tools and techniques to model and analyze highly reconfigurable distributed systems. In this paper, we present an integrated methodology to use the Credo tool suite. In this methodology, we advertise the use of top-down design, component-based modeling and compositional analysis to address the complexity of highly reconfigurable distributed systems. As a running example, we model a peer-to-peer file-sharing system and show how and when to apply the different modeling and analysis techniques of Credo.

This document is submitted as Annex 6.3.3 for the Deliverable D6.3 (Final Modelling of Biomedical Sensor Networks using the Creol Tools) of the EU project IST‐33826 CREDO: Modeling and analysis of evolutionary structures for distributed services. We describe how to model biomedical sensor networks using the CREDO methodology and the Creol Tools, specifically Creol, Vereofy, and UPPAAL. Properties from forwarding and routing as well as from the link‐ and network layers are put into focus. Modelling the AODV algorithm is presented in‐depth in this document. The outcome of this work will be used for the validation phase of CREDO to judge the suitability of the Creol Tools.

In this paper, we investigate the use of cooperative communications for reliable data dissemination in wireless sensor networks. We first identify the disadvantages of some existing cooperative schemes. While the previously proposed “multi-hop mesh cooperative transmission structure” addresses these disadvantages, it suffers from large end-to-end delays during data disseminations due to its random value-based forwarding node selection scheme. This paper proposes a novel distance-based forwarding node selection scheme that yields smaller end-to-end delays. We present extensive simulation results that verify the effectiveness of the proposed data dissemination scheme.

Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of adaptivity, reliability and network throughput. In this paper, we investigate the use of cooperative communications with adaptive relay selection for resource-constrained wireless sensor networks, and propose QoS-RSCC, a QoS-support multi-agent reinforcement learning based relay selection scheme for cooperative communications. In QoS-RSCC, optimal relays, in terms of outage probability and channel efficiency, are selected distributedly from multiple relaying candidates for the intermediate routers along the multi-hop route, without the needs of prior knowledge of the wireless network model and centralized control. We compare the network performance of QoS-RSCC with CRP [1], and investigate the impacts of network traffic load, channel bit error rate, and node's mobility on the network performance. Simulation results show that QoS-RSCC can achieve a near-optimal performance on both diversity gains and channel efficiency, and fits well in dynamic environments.

Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of adaptivity, reliability, data throughput and network life time. In this paper, we investigate the use of cooperative communications for quality of service (QoS) provisioning in resource-constrained wireless sensor networks, and propose MRL-CC, a Multi-agent Reinforcement Learning based multi-hop mesh Cooperative Communication mechanism for wireless sensor networks. In order to disseminate data reliably in MRL-CC, a multi-hop mesh cooperative structure is first constructed. Then a cooperative mechanism with cooperative partner assignments, and coding and transmission schemes is implemented using a multi-agent reinforcement learning algorithm. We compare the network performance of MRL-CC with MMCC [1], a Multi-hop Mesh structure based Cooperative Communication scheme, and investigate the impacts of network traffic load, interference and sensor node's mobility on the network performance. Simulation results show that MRL-CC performs well in terms of a number of QoS metrics, and fits well in large-scale networks and highly dynamic environments.

In this paper, we present MRL-QRP, a multi-agent reinforcement learning based routing protocol with QoS support for wireless sensor networks. In MRL-QRP, sensor node cooperatively computes QoS routes using a distributed value function - distributed reinforcement learning algorithm (DVFDRL). Global optimization can be achieved by using locally observed network information and limited exchanging of state values with immediate neighboring nodes. We compare the network performance of MRL-QRP with QoS-AODV, an on demand QoS support routing protocol. The impact of network traffic load and sensor node’s mobility on the network performance are investigated, simulation results show that MRL-QRP performs well in respects of a number of QoS metrics and fits well in highly dynamic environments.