Biologically-inspired approaches are one of the most promising approaches to realize highly-adaptive distributed systems. Biological systems inherently have self-* properties, such as self-stabilization, self-adaptation, self-configuration, self-optimization and self-healing. Thus, the application of biological systems into distributed systems has attracted a lot of attention recently. In this paper, we present one successful result of bio-inspired approach: we propose distributed algorithms for resource replication inspired by the single species population model. Resource replication is a crucial technique for improving system performance of distributed applications with shared resources. In systems using resource replication, generally, a larger number of replicas lead to shorter time to reach a replica of a requested resource but consume more storage of the hosts. Therefore, it is indispensable to adjust the number of replicas appropriately for the resource sharing application. This paper considers the problem for controlling the densities of replicas adaptively in dynamic networks and proposes two bio-inspired distributed algorithms for the problem. In the first algorithm, we try to control the replica density for a single resource. However, in a system where multiple resources coexist, the algorithm needs high network cost and the exact knowledge at each node about all resources in the network. In the second algorithm, the densities of all resources are controlled by the single algorithm without high network cost and the exact knowledge about all resources. This paper shows by simulations that these two algorithms realize self-adaptation of the replica density in dynamic networks.

Wireless LANs, which consist of access points and wireless stations, have widely spread in recent years. Routing in wireless LANs suffers the problem that each wireless station selects an access point and a wired path to its destination station. It is desired to design an adaptive routing protocol for wireless LANs since throughputs of communications are dynamically affected by selections of other wireless stations and external environmental changes. In this paper, we propose a routing protocol for wireless LANs based on attractor selection. Attractor selection is a biologically inspired approach, and it has high adaptability to dynamic environmental changes. By applying attractor selection, each wireless station can adaptively select its access point and wired path with high throughput against environmental changes. In addition, we design the protocol with a new technique: combination of multiple attractor selections. The technique is useful because it enables us to divide a problem into several simpler problems. To the best of our knowledge, our protocol is the first one designed around a combination of multiple attractor selections. We show the effectiveness and adaptability of our protocol by simulations.

In this paper we propose the Zone-based Energy Aware data coLlection (ZEAL) protocol. ZEAL is designed to be used in agricultural applications for wireless sensor networks. In these type of applications, all data is often routed to a single point (named “sink” in sensor networks). The overuse of the same routes quickly depletes the energy of the nodes closer to the sink. In order to minimize this problem, ZEAL automatically creates zones (groups of nodes) independent from each other based on the trajectory of one or more mobile sinks. In this approach the sinks collects data queued in sub-sinks in each zone. Unlike existing protocols, ZEAL accomplish its routing tasks without using GPS modules for location awareness or synchronization mechanisms. Additionally, ZEAL provides an energy saving mechanism on the network layer that puts zones to sleep when there are no mobile sinks nearby. To evaluate ZEAL, it is compared with the Maximum Amount Shortest Path (MASP) protocol. Our simulations using the ns-3 network simulator show that ZEAL is able to collect a larger number of packets with significantly less energy in the same amount of time.

The gathering problem of anonymous and oblivious mobile robots is one of the fundamental problems in the theoretical mobile robotics. We consider the gathering problem in unoriented and anonymous rings, which requires that all robots eventually keep their positions at a common non-predefined node. Since the gathering problem cannot be solved without any additional capability to robots, all the previous results assume some capability of robots, such as the agreement of local view. In this paper, we focus on the multiplicity detection capability. This paper presents a deterministic gathering algorithm with local-weak multiplicity detection, which provides a robot with information about whether its current node has more than one robot or not. This assumption is strictly weaker than that in previous works. Our algorithm achieves the gathering from an aperiodic and asymmetric configuration with 2 < k < n/2 robots, where n is the number of nodes. We also show that our algorithm is asymptotically time-optimal one, i.e., the time complexity of our algorithm is O(n). Interestingly, despite the weaker assumption, it achieves significant improvement compared to the previous algorithm, which takes O(kn) time for k robots.