Energy conservation in Wireless Sensor Networks Sagnik Bhattacharya, Tarek Abdelzaher DARPA ITO University of Virginia, Department of Computer Science National Science School of Engineering and Applied Science, Charlottesville, VA 22903 Foundation Office of Naval http://www.cs.virginia.edu/nest Research Sensor Network Applications Towards efficient Wireless Sensor Networks Tiny Sensor Nodes In recent years, wireless sensor networks have emerged as a new fast-growing application domain for distributed computing . The vision of sensor networks presents new and unique challenges arising from the highly constrained resources of individual sensor-equipped nodes, and the large scale of the overall network. Power is identified as the most expensive resource in a sensor network. In most cases, such networks are meant for one- time use, i.e., once the battery dies, the node dies too. Hence, maximizing network lifetime by conserving power is a matter of great importance. Our approach is to develop middleware to •4 Mhz, 8 bit MCU (Amtel), 512 bytes RAM, 8K ROM conserve energy and give the base-stations the abstractions of a •900 Mhz radio (RF Monolithics) 10-100 ft. range network virtual machine embedded in the network. Middleware for Sensor Networks Data Placement and Replication Middleware Application Inspired by web caching and multicast technologies, our data placement middleware creates and places replicas of requested data so that communication Middleware is minimized. According to the request rates and the update rates of the data a Data Placement In-network aggregation Sensor Power hierarchy of replicas are created such that the depth of the hierarchy adapts with / Replication / Group Consensus Interface Management change in request and update rates. - Base-station Location Service Location-aware Routing 1 i - Level-i copy 2 - Sensor MAC / Wireless Broadcast communication 1 3 1 The sensor nodes run on a battery which limits their lifetime. Experimental results 2 have shown that wireless packet communication consumes most of the energy of a 2 mode. Hence reducing the amount of communication shall result in increased network lifetime. The middleware allows the sensor nodes to conserve energy in an aggregated and distributed manner. The main attributes of the middleware are: Energy Conservation, Scalability, Portability, Consistency, Reduced In general, when the environment is placid and the update rate is low, more Communication Overhead, Decentralized computation and Resource copies are created, and when the environment is volatile and the update rate Allocation. is high, consolidation takes place and the number of copies is reduced. In general the depth of the copy tree is equal to Rmax / Rupdate. Event detection by in-network aggregation The data placement When an event such as an explosion occurs, individual sensor values like Application Copy/Senso Copy table Redirect middleware causes the temperature, light etc, by themselves may not be of interest to the applications, r data (at sensor) table location-directed queries from (at sensor) (at base- but taken together, the macro-information (i.e., explosion) is much more relevant. station) the application to be redirected We use dynamically-programmable rules, distributed arbitrarily in the sensor Data Placement to the copy locations using the Middleware Cache redirect table. These redirect network to identify and triangulate the location of the events. Copy Message table Handlers queries get served by the At this step, clusters are formed Example of a rule: Routing / copies which are stored in the dynamically within the region (Temperature>500) and (Light>100) Location service cache at certain locations. where the sensors pick up => Explosion. abnormal values, and a cluster If (T= 600) and (L=200) then A tree of replicas of the sensor data is formed, and in general a base-station with a leader is elected. No node can Explosion = true and confidence = request rate R gets served by a level-⎣R / Rupdate⎦ copy. Whenever an update belong to more than one cluster. (600-500)/500 + (200-100)/100 = 1.2 occurs it gets propagated along the copy tree. Experimental Results Single Event Cluster Rule Data Value Our experimental results Formation Evaluation Aggregation 16 Aggregation Average Dissipated Energy (Joules/node/flow) (using ns-2 simulator) show Data Placement 14 No Data Placement that our data placement 12 Omniscient Multicast strategy provides At this stage, clusters In the final stage, the 10 considerable energy savings At this stage all the evaluate the rules among cluster leaders and is quite close to the sensors of a single type themselves. Each node communicate amongst 8 optimal omniscient multicast (e.g.., temperature) may not have the necessary themselves and use the 6 for the case when the request come to a consensus so rule which evaluates to confidence values of the rates are greater than the 4 that each node in a true given the data, but individual clusters to update rate, but does not cluster has exactly the eventually the identified pinpoint the location of the 2 show the degradation in same value for event and confidence is events. The final data 0 performance shown by 0 1 2 3 4 5 6 different types of transmitted to the cluster about the event type and 1 / Sensor Update rate (normalized) omniscient multicast when sensors. leader. location are propagated to the update rate becomes greater. It gracefully consolidates the copies as the the base-stations update rate increases, until it reaches a point when no copies are created.
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