Intensive research has been conducted on data aggregation routing, but the important MAC layer retransmission issue as described above has been relatively selleck chemicals seldom addressed. Krishnamachari [5] devises three interesting suboptimal aggregation heuristics, called Shortest Paths Tree (SPT), Center at Nearest Source (CNS), and Greedy Incremental Tree (GIT), respectively. In the SPT scheme, each data source node finds the shortest path back to the sink node. The CNS Inhibitors,Modulators,Libraries scheme selects one node that is the nearest to the sink node as the aggregation node and other data source nodes connect to this aggregation node by using respective Inhibitors,Modulators,Libraries shortest hop paths. And in the GIT scheme, initially the member(s) in the tree is only the sink node.
Each data source finds a shortest hop path to this tree and the data sources with the minimum hop along with the intermediate nodes on this path are included in this tree. This process is repeated until all data source nodes Inhibitors,Modulators,Libraries are included in the tree. In [6], they propose centralized heuristic based on the Prim’s minimal cost spanning tree algorithm to construct a data aggregation tree. This heuristic incorporates residual energy of sensor nodes into the Prim’s algorithm in order to prolong the lifetime of sensor nodes. In [2], they propose a rigorous mixed integer mathematical fo
This survey provides an overview of wireless sensor network (WSN) connectivity, and discusses existing work that focuses on the connectivity issues in WSNs. In particular, we are interested in maintaining connected WSNs and their connectivity related characteristics including sensor node placement, as well as the construction of a small connected relay set in WSNs.
We aim to review extensively the existing results related to these topics, and stimulate new research.Sensor networks have Inhibitors,Modulators,Libraries a long history, AV-951 which can be traced back as far as the 1950′s. It is recognized that the first obvious sensor network was the Sound Surveillance System (SOSUS) [1, 2]. The SOSUS was made up of an array of acoustic sensors that were interconnected by wired cables and were deployed by the US in deep ocean basins during the Cold War to detect and track Soviet submarines. In its early stages, the development of sensor networks was mainly driven by military use, in which sensor nodes were wired together to provide battlefield surveillance.
Evolution of technologies has driven sensor networks away from their original appearance. With the emergence of integrated sensors embedded with wireless capability, most of current sensor networks consist of a collection of wirelessly interconnected sensors, each of which is embedded with sensing, computing and communication components. These selleck compound sensors can observe and respond to phenomena in the physical environment [3]. Such sensor networks are referred to as wireless sensor networks (WSNs).
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