NDLI: An OS for Mobile Ad hoc Networks Using Ant Based Hueristic to Distribute Mobile Services

Content Provider	IEEE Xplore Digital Library
Author	Heimfarth, T. Danne, K. Rammig, F.J.
Copyright Year	2005
Description	Author affiliation: Paderborn Univ. (Heimfarth, T.; Danne, K.; Rammig, F.J.)
Abstract	This paper presents the architecture of an operating system (called NanoOS) for applications distributed over mobile ad hoc networks (MANETs). Furthermore, a service distribution method inspired on the foraging behavior of ants is proposed. The NanoOS offers an uniform, environment of execution where the movement of nodes is transparent to the tasks. Moreover, the code of the OS is distributed among the nodes in order to support complex services while keeping the footprint small on each node. We propose a swarm optimization based heuristic to control the migration of the OS (and application) services in order to reduce the communication overhead. Each service request leaves pheromone in the nodes within its path to the service provider. An optimization step occurs when the service provider migrates to the neighbor node with the higher pheromone concentration. Realized simulations have shown that our heuristic performs well. The total communication cost in average is just 40% higher than the global optimum obtained using branch and bound, while a random, distribution of services result in a cost about 350% higher than the optimum. Moreover, our algorithm just uses local information and has a very low computational requirement
Starting Page	77
Ending Page	77
File Size	5047933
Page Count	1
File Format	PDF
ISBN	0769524508
DOI	10.1109/ICAS-ICNS.2005.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-23
Publisher Place	French Polynesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Energy consumption Operating systems Cost function Ad hoc networks Hardware Nanoscale devices Resource management Particle swarm optimization Mobile ad hoc networks
Content Type	Text
Resource Type	Article

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