Abstract
When physical communication network infrastructures fail, infrastructure-less communication networks such as mobile ad-hoc networks (MANET), can provide an alternative. This, however, requires MANETs to be adaptable to dynamic contexts characterized by the changing density and mobility of devices and availability of energy sources. To address this challenge, this paper proposes a decentralized context-adaptive topology control protocol. The protocol consists of three algorithms and uses preferential attachment based on the energy availability of devices to form a loop-free scale-free adaptive topology for an ad-hoc communication network. The proposed protocol has a number of advantages. First, it is adaptive to the environment, hence applicable in scenarios where the number of participating mobile devices and their availability of energy resources is always changing. Second, it is energy-efficient through changes in the topology. This means it can be flexibly combined with different routing protocols. Third, the protocol requires no changes on the hardware level. This means it can be implemented on all current phones, without any recalls or investments in hardware changes. The evaluation of the protocol in a simulated environment confirms the feasibility of creating and maintaining a self-adaptive ad-hoc communication network, consisting of multitudes of mobile devices for reliable communication in a dynamic context.
Highlights
Connectivity is essential to today’s society, and relies heavily on the availability and reliability of physical network infrastructures (Sterbenz et al 2010)
To ensure efficient mobile ad-hoc networks (MANET) deployment, adaptive use of available energy resources is required within such dynamic contexts (Vanjale et al 2018; Conti and Giordano 2014)
To address this challenge this paper proposes a decentralized adaptive topology control protocol consisting of three algorithms
Summary
Connectivity is essential to today’s society, and relies heavily on the availability and reliability of physical network infrastructures (Sterbenz et al 2010). The relaying node looks for new connections in its transmission range to connect with the highest battery charge left belonging to a different network. The transmission range, residual battery capacity, the cost of sending, receiving, and relaying messages, and the cost of reconfiguration are all based on empirical results for BLE 5.0 (Texas Instruments 2018) on mobile devices.
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