Based on Pause Time Comparative Analysis made among Bee-Ant Colony Optimized Routing (BACOR) Vs Existing Routing Protocols for Scalable Mobile Ad Hoc Networks (MANETs)

In this paper based on swarm intelligence a new approach for an on demand ad-hoc routing algorithm is proposed. The foraging behavior of Ant colony optimization and Bee colony optimization, which are the subset of swarm intelligence and considering the ability of simple ants to solve complex problems by cooperation. Several algorithms which are based on ant colony problems were introduced in the literatures to solve different problems, e.g., optimization problems. The proposed algorithm is compared and proven by results that the approach has the potential to become an appropriate routing tactics for mobile ad-hoc networks. The results were presented based on the simulations made with the implementation in ns-2. Keywords:BACOR, Bee Routing, Ant Routing, Bee-Ant Routin

Convergence Results for Ant Routing Algorithms via Stochastic Approximation and Optimization

``Ant algorithms'' have been proposed to solve a variety of problems arising in optimization and distributed control. They form a subset of the larger class of ``Swarm Intelligence'' algorithms. The central idea is that a "swarm" of relatively simple agents can interact through simple mechanisms and collectively solve complex problems. Instances that exemplify the above idea abound in nature. The abilities of ant colonies to collectively accomplish complex tasks have served as sources of inspiration for the design of ``Ant algorithms''. Examples of ``Ant algorithms'' are the set of ``Ant Routing'' algorithms that have been proposed for communication networks. We analyze in this paper Ant Routing Algorithms for packet-switched wireline networks. The algorithm retains most of the salient and attractive features of Ant Routing Algorithms. The scheme is a multiple path probabilistic routing scheme, that is fully adaptive and distributed. Using methods from adaptive algorithms and stochastic approximation, we show that the evolution of the link delay estimates can be closely tracked by a deterministic ODE system. A study of the equilibrium points of the ODE gives us the equilibrium behavior of the routing algorithm, in particular, the equilibrium routing probabilities, and mean delays in the links under equilibrium. We also show that the fixed-point equations that the equilibrium routing probabilities satisfy are actually the necessary and sufficient conditions of an appropriate optimization problem. Simulations supporting the analytical results are provided.Research supported by the U.S. Army Research Laboratory under the CTA C & N Consortium Coop. Agreement DAAD19-01-2-0011 and by the U.S. Army Research Office under MURI01 Grant No. DAAD19-01-1-0465

Ant routing algorithm for the Lightning Network

We propose a decentralized routing algorithm that can be implemented in Bitcoin Lightning Network. All nodes in the network contribute equally to path searching. The algorithm is inspired from ant path searching algorithms.Comment: 10 pages, 1 figur

Hybrid 2-stage Imperialist Competitive Algorithm with Ant Colony Optimization for Solving Multi-Depot Vehicle Routing Problem.

The Multi-Depot Vehicle Routing Problem (MDVRP) is a real-world model of the simplistic Vehicle Routing Problem (VRP) that considers how to satisfy multiple customer demands from numerous depots. This paper introduces a hybrid 2-stage approach based on two population-based algorithms - Ant Colony Optimization (ACO) that mimics ant behaviour in nature and the Imperialist Competitive Algorithm (ICA) that is based on geopolitical relationships between countries. In the proposed hybrid algorithm, ICA is responsible for customer assignment to the depots while ACO is routing and sequencing the customers. The algorithm is compared to non-hybrid ACO and ICA as well as four other state-of-the-art methods across 23 common Cordreaus benchmark instances. Results show clear improvement over simple ACO and ICA and demonstrate very competitive results when compared to other rival algorithms

Secure and robust multi-constrained QoS aware routing algorithm for VANETs

Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In Vehicular Ad hoc Networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the Ant Colony Optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented Evolving Graph (VoEG) model to perform plausibility checks on the exchanged routing control messages among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service