(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 4, 2013 87 | Page www.ijacsa.thesai.org A Review of Computation Solutions by Mobile Agents in an Unsafe Environment Anis Zarrad Department of Computer Science and Information Systems Prince Sultan University, Riyadh, Saudi Arabia Yassine Daadaa College of Computer and Information Sciences Al-Imam Muhammad ibn Saud Islamic University, Riyadh, Saudi Arabia Abstract—Exploration in an unsafe environment is one of the major problems that can be seen as a basic block for many distributed mobile protocols. In such environment we consider that either the nodes (hosts) or the agents can pose some danger to the network. Two cases are considered. In the first case, the dangerous node is a called black hole, a node where incoming agents are trapped, and the problem is for the agents to locate it. In the second case, the dangerous agent is a virus; an agent moving between nodes infecting them, and the problem is for the “good” agents to capture it, and decontaminate the network. In this paper, we present several solutions for a black–hole and network decontamination problems. Then, we analyze their efficiency. Efficiency is evaluated based on the complexity, and the effort is in the minimization of the number of simultaneous decontaminating elements active in the system while performing the decontamination techniques. Keywords—Distributed algorithm; Mobile Agent; Network Decontamination; Black Hole Search; and Network Exploration I. INTRODUCTION Today’s need to maintain network protection practices and challenges in the universe are interconnected. Virus protection represents a rising importance in network decontamination methods. Faults and viruses often spread in networked environments, where nodes represent hosts and edges represent connections between hosts, by propagating from neighboring sites. Such a topic is known as exploration in unsafe environment. Exploration consists of having a set of agents collaboratively traverse an unknown network to collect relevant information. Network exploration has been extensively studied over the past fifty years due to its various applications in different areas such as engineering, computer science, and applied mathematics. Two major problems are discussed in this work; black-hole and network decontamination. In network contamination, a node might behave incorrectly, and it could affect its neighbor to become contaminated as well, thus propagating faulty computations. The propagation patterns of faults can follow different dynamics, depending on the behavior of the affected site. In this work we begin by giving a general overview about network exploration in unsafe environment and its applications. The rest of the paper is organized as follows. First, we summarize the backgrounds and related works, second we review some of the major solutions to date and their classification, and finally in section four we offer a conclusion. II. BACKGROUNDS AND RELATED WORKS The main focus in this work is computation solutions by mobile agents in an unsafe environment. Also, we believe there is a need to highlight the most influential works related to mobile agent systems that occurred in the past in order to give credit to founder researches. The problem of exploration is well known, where agents need to collaborate in order to explore an unknown environment. For example, tasks in environments that is not suitable for human operation, navigating a robot through a terrain containing obstacles, and finding a path through a maze. In recent years, application such as searching for data stored at unknown nodes in a computer network using mobile software agents, and obtaining maps of existing networks (e.g., computer networks, sewage systems, unexplored caves) have been studied. Map construction is the related problem of exploring the network to return an exact map of its topology. Previous work on exploration of labeled graphs has emphasized minimizing the cost of exploration in terms of the total number of edge traversals (moves), and the amount of memory used by the agent [1, 2, 12, 13, 38]. In [2], Awerbuch et al. studied how a mobile robot can learn an unknown environment in a piecemeal manner. The robot's goal is to learn a complete map of its environment, while satisfying the constraint that it must return every so often to its starting position (e.g., for refuelling). Exploration of anonymous graphs is impossible if marking of the nodes is not allowed in some way. An exception is when the graph is acyclic, meaning the graph is a tree [14, 30]. Different models for marking the nodes have been used to solve the exploration problem. Pebbles which can be dropped and removed from a node was proposed by Bender et al. in [5], where it was shown that one pebble is enough to explore the graph if the robot knows an upper bound on the size of the graph, and (log log n) pebbles are necessary and sufficient otherwise. Among the various possible techniques of decontamination, two types have been identified in the literature [24] internal and external decontamination. In internal decontamination a site can decontaminate itself (i.e., it can activate an antiviral software) when a certain condition of the neighborhood is verified. A clean site gets re- contaminated when some other condition of the neighboring