Data Gathering Algorithms in Sensor Networks Using Energy Metrics

• Authors: Stephanie Lindsey;Cauligi Raghavendra;Krishna M. Sivalingam
• Venue: IEEE Transactions on Parallel and Distributed Systems
• Year: 2002

Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operating the sensor network for a long period of time. A data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. There is some fixed amount of energy cost in the electronics when transmitting or receiving a packet and a variable cost when transmitting a packet which depends on the distance of transmission. If each node transmits its sensed data directly to the base station, then it will deplete its power quickly. The LEACH protocol presented is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster-heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. An improved version of LEACH, called LEACH-C, is presented , where the central base station performs the clustering to improve energy efficiency. In this paper, we present an improved scheme, called PEGASIS (Power-Efficient GAthering in Sensor Information Systems), which is a near-optimal chain-based protocol that minimizes energy. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 200 percent when 1 percent, 25 percent, 50 percent, and 100 percent of nodes die for different network sizes and topologies. For many applications, in addition to minimizing energy, it is also important to consider the delay incurred in gathering sensed data. We capture this with the \big. energy \times delay\bigr. metric and present schemes that attempt to balance the energy and delay cost for data gathering from sensor networks. Since most of the delay factor is in the transmission time, we measure delay in terms of number of transmissions to accomplish a round of data gathering. Therefore, delay can be reduced by allowing simultaneous transmissions when possible in the network. With CDMA capable sensor nodes, simultaneous data transmissions are possible with little interference. In this paper, we present two new schemes to minimize \big. energy \times delay\bigr. using CDMA and non-CDMA sensor nodes. If the goal is to minimize only the delay cost, then a binary combining scheme can be used to accomplish this task in about \big. \log N\bigr. units of delay with parallel communications and incurring a slight increase in energy cost. With CDMA capable sensor nodes, a chain-based binary scheme performs best in terms of \big. energy \times delay\bigr.. If the sensor nodes are not CDMA capable, then parallel communications are possible only among spatially separated nodes and a chain-based 3-level hierarchy scheme performs well. We compared the performance of direct, LEACH, and our schemes with respect to \big. energy \times delay\bigr. using extensive simulations for different network sizes. Results show that our schemes perform 80 or more times better than the direct scheme and also outperform the LEACH protocol.