Extensive empirical studies presented in this article confirm that the quality of radio communication between low-power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This article presents ATPC, a lightweight algorithm for Adaptive Transmission Power Control in wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations over a long period of time. The results from the real-world experiments demonstrate that (1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability, and (2) with online control, ATPC is robust even with environmental changes over time.

ATPC: Adaptive Transmission Power Control for Wireless Sensor Networks

The recent technological advances in micro electro-mechanical systems have promoted the development of a powerful class of sensor-based distributed intelligent systems capable of ubiquitously retrieving multimedia information, namely Wireless Multimedia Sensor Networks (WMSNs). WMSNs are gaining more popularity day by day as they are envisioned to support a large number of both non-real time and real-time multimedia applications. However, satisfying the stringent quality of service (QoS) requirements of multimedia transmission in a resource-constrained sensor network environment places new challenges to routing. As an outcome, optimal energy and application-specific QoS aware routing for WMSNs has gained considerable research attention recently. In this paper, current state-of-the-art in energy-efficient routing techniques for WMSNs is surveyed together with the highlights of the performance issues of each strategy. We outline the design challenges of routing protocols for WMSNs followed by the limitations of current techniques designed for non-multimedia data transmission. Further, a classification of recent routing protocols for WMSNs and a discussion of possible future research trends are presented.

A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless Multimedia Sensor Networks

Recent research shows that significant energy saving can be achieved in wireless sensor networks with a mobile base station that collects data from sensor nodes via short-range communications. However, a major performance bottleneck of such WSNs is the significantly increased latency in data collection due to the low movement speed of mobile base stations. To address this issue, we propose a rendezvous-based data collection approach in which a subset of nodes serve as the rendezvous points that buffer and aggregate data originated from sources and transfer to the base station when it arrives. This approach combines the advantages of controlled mobility and in-network data caching and can achieve a desirable balance between network energy saving and data collection delay. We propose two efficient rendezvous design algorithms with provable performance bounds for mobile base stations with variable and fixed tracks, respectively. The effectiveness of our approach is validated through both theoretical analysis and extensive simulations.

/pdf/rendezvous-design-algorithms-for-wireless-sensor-networks-4cdr04xhyc.pdf

Rendezvous design algorithms for wireless sensor networks with a mobile base station

Operating profiles for consumers of computing resources may be automatically determined based on an analysis of actual resource usage measurements and other operating metrics. Measurements may be taken while a consumer, such as a virtual machine instance, uses computing resources, such as those provided by a host. A profile may be dynamically determined based on those measurements. Profiles may be generalized such that groups of consumers with similar usage profiles are associated with a single profile. Assignment decisions may be made based on the profiles, and computing resources may be reallocated or oversubscribed if the profiles indicate that the consumers are unlikely to fully utilize the resources reserved for them. Oversubscribed resources may be monitored, and consumers may be transferred to different resource providers if contention for resources is too high.

Automated profiling of resource usage

The vision of wireless multimedia sensor networks (WMSNs) is to provide real-time multimedia applications using wireless sensors deployed for long-term usage. Quality of service assurances for both best effort data and real-time multimedia applications introduced new challenges in prioritizing multipath routing protocols in WMSNs. Multipath routing approaches with multiple constraints have received considerable research interest. In this paper, a comprehensive survey of both best effort data and real-time multipath routing protocols for WMSNs is presented. Results of a preliminary investigation into design issues affecting the development of strategic multipath routing protocols that support multimedia data in WMSNs are also presented and discussed from the network application perspective.

A Survey on Multipath Routing Protocols for QoS Assurances in Real-Time Wireless Multimedia Sensor Networks

Many wireless sensor network applications must resolve the inherent conflict between energy efficient communication and the need to achieve desired quality of service such as end-to-end communication delay. To address this challenge, we propose the Real-time Power-Aware Routing (RPAR) protocol, which achieves application-specified communication delays at low energy cost by dynamically adapting transmission power and routing decisions. RPAR features a power-aware forwarding policy and an efficient neighborhood manager that are optimized for resource-constrained wireless sensors. Moreover, RPAR addresses important practical issues in wireless sensor networks, including lossy links, scalability, and severe memory and bandwidth constraints. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadlines missed and energy consumption compared to existing real-time and energy-efficient routing protocols.

/pdf/real-time-power-aware-routing-in-sensor-networks-502x78dk17.pdf

Real-time Power-Aware Routing in Sensor Networks

Many mission-critical wireless sensor network applications must resolve the inherent conflict between the tight resource constraints on each sensor node, particularly in terms of energy, with the need to achieve desired quality of service such as end-to-end real-time performance. To address this challenge we propose the Real-time Power-Aware Routing (RPAR) protocol. RPAR achieves required communication delays at minimum energy cost by dynamically adapting the transmission power and routing decisions based on packet deadlines. RPAR integrates a geographic forwarding policy cognizant of deadlines, power, and link quality with new algorithms for on-demand power adaptation and efficient neighborhood discovery. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadline misses and energy consumption when compared to existing real-time and energyefficient routing protocols and beacon based neighborhood management schemes.

/pdf/real-time-power-aware-routing-in-wireless-sensor-networks-1wwbmfvlt5.pdf

Real-time Power Aware Routing in Wireless Sensor Networks

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Real-time Power-Aware Routing in Sensor Networks

Real-time Power Aware Routing in Wireless Sensor Networks