Abstract
This paper introduces a method for deployment-specific adaptation of wireless ad hoc networks. The method utilizes sophisticated nodes which model the network signature for actual deployments and routing paths. Since the transmit power is fixed, many nodes may not save energy from communication. At the same time, all nodes save energy from calculations and the number of beacon periods may be controlled. The nodes with embedded simulators control the balance between lifetime and real-time performance. Also, some routes are modified to decline the communication range and save energy. An example shows a significant energy reduction and improved real-time performance.
Highlights
Ad hoc networks have a wide spectrum of military and commercial applications
There is a class of ad hoc networks, sensor networks, where the requirements for lifetime and size of the nodes are driven to extremes
A wireless sensor network consists of a large number of nodes that may be randomly and densely deployed
Summary
Ad hoc networks have a wide spectrum of military and commercial applications. Ad hoc networks are employed in situations where installing an infrastructure is too expensive, too vulnerable or the network is transient. There is a class of ad hoc networks, sensor networks, where the requirements for lifetime and size of the nodes are driven to extremes. Sensor network nodes execute three major tasks: sensing, computation and communication. Real-time forwarding of packets under multihop communication scheme is a serious challenge. The multihop nature of ad hoc networks, while beneficial for energy reduction, brings the packets delivery time up. The dynamic nature of the network and the power-efficient partitioning of communication links in particular, often result in unpredictable traffic timing parameters. Ad hoc network simulators are used to study the major parameters such as throughput, real-time and lifetime performance. In this paper we consider heterogeneous sensor networks where sophisticated nodes execute basic simulation tasks. Simulation results are employed to dynamically adapt the network to changing requirements
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