Firefly groups perform a distributed synchronization of their flashing behavior and this is applied to synchronization in sensor networks [5]. Reaction-diffusion describes the chemical dynamics novel of morphogens in the development of stripes or spots on animal furs. Based on the reaction-diffusion dynamics, the coding rate for camera sensor networks can be controlled [6].Since biological systems are often described as dynamic systems, they rely on a mathematical formulation given as differential equations. In dynamic systems, attractors describe the states to which the system evolves over time. In the past, we studied the concept of attractor selection, which is based on the dynamics found in gene expression [7] and has been previously also applied to tackle problems in communication networks [8, 9].

In this paper, we apply a similar biological mechanism called attractor perturbation (AP), which is derived from the fluctuation-response relationship observed in an experiment on the evolution of functional proteins in a cell [10]. A previous application of AP to computer networks can be found in [11, 12].In this paper, we focus on bandwidth improvement and end-to-end delay minimization in ad hoc networks. In terms of bandwidth improvement, one of the most common approaches is to use multiple paths in the same or across different media (multihoming). To enable the ability to utilize multiple paths concurrently, there is some existing work in both wired, for example, opportunistic multipath scheduling (OMS) [13], and wireless networks, for example, concurrent multipath transfer (CMT) [14, 15] and adaptive load balancing algorithm (ALBAM) [16].

However, most existing control methods require a full knowledge of the current network status, for example, queue length on each node, which is difficult to obtain or requires frequent probing causing bandwidth degradation. Therefore, we apply AP to concurrent multipath traffic distribution to improve the available bandwidth while utilizing the AP relationship to predict the outcome of the traffic adjustment and also minimize the end-to-end delay at the same time.The contributions of this paper are as follows. First is the end-to-end characteristics of the AP-based proposal, which allows easy deployment in existing networks without the need of modifying all intermediate nodes. Second is the usage of statistical information, which consumes less bandwidth to obtain Anacetrapib than using probing results. Third is the ability to provide a simplified view of the network as a black box with only the end-to-end observed variables while maintaining the ability to influence the network performance.