Many wireless sensor networks must sustain long lifetimes on limited energy resources. Two major approaches, transmission power control and sleep scheduling, have been proposed to reduce the radio power consumption in the transmission state and the idle state, respectively. In this paper, we first review existing transmission power control and sleep scheduling approaches and then describe a Unified Radio Power Management framework for the design and implementation of holistic radio power management solutions in wireless sensor networks. It has two key components: (1) a novel optimization approach called Minimum Power Configuration that minimizes the aggregate radio power consumption of all ratio states and (2) a Unified Power Management Architecture (UPMA) that aims to support the flexible cross-layer integration of different power management strategies. A novel feature of UPMA is that it enables cross-layer coordination and joint optimization of different power management strategies that exist at multiple network layers. Copyright © 2008 John Wiley & Sons, Ltd.

/pdf/towards-unified-radio-power-management-for-wireless-sensor-3pwj49jj2h.pdf

Towards unified radio power management for wireless sensor networks

In this paper, we study the performance of location-centric storage (LCS) theoretically. Our results indicate that LCS utilizes network resource efficiently. In particular, the storage load of sensors is independent of the network size, and is evenly distributed across the network. Moreover, the communication distance for getting event information is small. Therefore, the protocol has great scalability. In addition, we also propose algorithms for data retrieval in LCS. Our analysis shows that both the number of queries and the response cost involved in the algorithms could approach to the theoretical lower bound.

/pdf/on-the-performance-of-location-centric-storage-in-sensor-52s7gzufzo.pdf

On the Performance of Location-Centric Storage in Sensor Networks

http://tchinfo.ttu.edu.tw/download/grid.pdf?author=whliao&id=13343&fname=grid.pdf

A grid-based dynamic load balancing approach for data-centric storage in wireless sensor networks

This paper proposes a dynamic geographic hash table for data-centric storage (DCS) in sensor networks. In DCS systems, data storage locations are determined by data name. The storage locations are obtained through the use of a geographic hash table (GHT) that maps data names to geographic locations. Traditional DCS systems use a static hash function for this purpose, resulting in a static set of nodes serving the network throughout its lifetime. Hence, these nodes may experience unbalanced resource utilization problems and the network will not be capable of dealing with network dynamics such as new sensor deployments or runtime sensor failures. We address these problems by proposing a dynamic GHT solution that relies on two schemes: 1) a temporal-based geographic hash table to achieve overall load balancing among sensor nodes over time; and 2) a location selection scheme based on node contribution potential to proactively adapt the system to network dynamics. Our performance evaluations show that the dynamic GHT can alleviate the resource utilization problem of DCS systems and can prolong the network lifetime significantly

A dynamic geographic hash table for data-centric storage in sensor networks

Data Centric Storage (DCS) is a powerful storage paradigm for wireless ad hoc networks. In mobile ad hoc networks (MANETs), however, the mobility and varying density of nodes may significantly impact the efficiency of data access and the level of data consistency for existing DCS mechanisms. In this paper, we propose an efficient resilience mechanism for data centric storage that supports DCS in mobile environments. We introduce a novel indirection strategy that enables us to distinguish the storage of data at dedicated server nodes from the storage of additional information to locate these servers. Our approach places server location information dynamically in strategic parts of the network based on its current topology. Combining our server location advertisement with any geographic routing protocol, we provide a robust data update and query processing technique for data centric storage in MANETs. We show analytically and by means of experimental evaluations that, despite the additional indirection during packet forwarding, our approach provides superior storage and retrieval performance than the original DCS algorithm even for large amounts of dynamic data.

/pdf/an-efficient-resilience-mechanism-for-data-centric-storage-rs9jd58gwp.pdf

An Efficient Resilience Mechanism for Data Centric Storage in Mobile Ad Hoc Networks

In this paper, we present an efficient data centric storage method for wireless sensor networks with increased resiliency for single node failures as well as clustered node failures. We introduce multiple hashing to provide various resiliency levels for different event types, based on the event's criticality level. We also present a geometric area concept and node awareness inside the geometric shape to make our system independent of underlying routing. We present the two parts of routing from source to destination and shown our performance results.

An efficient resiliency scheme for data centric storage in wireless sensor networks

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An efficient resiliency scheme for data centric storage in wireless sensor networks