Adaptive Overlay Trees for Tradeoffs between Delay and Energy Consumption in Multicast on Static Ad Hoc Networks
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Multicasting is fundamental to many ad hoc network applications requiring collaboration of multiple nodes in a group. A general approach is to construct an overlay tree and to deliver a multicast packet to multiple receivers over the tree. This paper proposes adaptive overlay trees (AOTs) on wireless ad hoc networks of static nodes for delay- and energy-efficient multicast. A tradeoff function is derived, and an algorithm for AOT construction is developed. Note here that the requirements of delay and energy consumption may vary with different classes of applications. By adjusting parameters in the tradeoff function, different AOTs can be adaptively chosen for different classes of applications. An AOT is constructed in O(ke) time where e is the number of wireless links in a network and k is the number of member nodes in a multicast group. The simulation study shows that AOT adaptively provides tradeoffs between the fastest multicast (which is the choice if delay is the most important factor) and the most energy efficient multicast (which is used when energy consumption is the primary concern). In other words, one of AOTs can be appropriately chosen in accordance with the operation requirement.
Abstract
Multicasting is fundamental to many ad hoc network applications requiring collaboration of multiple nodes in a group. A general approach is to construct an overlay tree and to deliver a multicast packet to multiple receivers over the tree. This paper proposes adaptive overlay trees (AOTs) on wireless ad hoc networks of static nodes for delay- and energy-efficient multicast. A tradeoff function is derived, and an algorithm for AOT construction is developed. Note here that the requirements of delay and energy consumption may vary with different classes of applications. By adjusting parameters in the tradeoff function, different AOTs can be adaptively chosen for different classes of applications. An AOT is constructed in O(ke) time where e is the number of wireless links in a network and k is the number of member nodes in a multicast group. The simulation study shows that AOT adaptively provides tradeoffs between the fastest multicast (which is the choice if delay is the most important factor) and the most energy efficient multicast (which is used when energy consumption is the primary concern). In other words, one of AOTs can be appropriately chosen in accordance with the operation requirement.
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