An Incentive Mechanism for Cooperative Data Replication in MANETs - a Game Theoretical Approach

Wireless ad hoc networks have seen a great deal of attention in the past years, especially in cases where no infrastructure is available. The main goal in these networks is to provide good data accessibility for participants. Because of the wireless nodes' continuous movement, network partitioning occurs very often. In order to subside the negative effects of this partitioning and improve data accessibility and reliability, data is replicated in nodes other than the original owner of data. This duplication costs in terms of nodes' storage space and energy. Hence, autonomous nodes may behave selfishly in this cooperative process and do not replicate data. This kind of phenomenon is referred to as a strategic situation and is best modeled and analyzed using the game theory concept. In order to address this problem we propose a game theory data replication scheme by using the repeated game concept and prove that it is in the nodes' best interest to cooperate fully in the replication process if our mechanism is used

Towards Trustworthy, Efficient and Scalable Distributed Wireless Systems

Advances in wireless technologies have enabled distributed mobile devices to connect with each other to form distributed wireless systems. Due to the absence of infrastructure, distributed wireless systems require node cooperation in multi-hop routing. However, the openness and decentralized nature of distributed wireless systems where each node labors under a resource constraint introduces three challenges: (1) cooperation incentives that effectively encourage nodes to offer services and thwart the intentions of selfish and malicious nodes, (2) cooperation incentives that are efficient to deploy, use and maintain, and (3) routing to efficiently deliver messages with less overhead and lower delay. While most previous cooperation incentive mechanisms rely on either a reputation system or a price system, neither provides sufficiently effective cooperation incentives nor efficient resource consumption. Also, previous routing algorithms are not sufficiently efficient in terms of routing overhead or delay. In this research, we propose mechanisms to improve the trustworthiness, scalability, and efficiency of the distributed wireless systems. Regarding trustworthiness, we study previous cooperation incentives based on game theory models. We then propose an integrated system that combines a reputation system and a price system to leverage the advantages of both methods to provide trustworthy services. Analytical and simulation results show higher performance for the integrated system compared to the other two systems in terms of the effectiveness of the cooperation incentives and detection of selfish nodes. Regarding scalability in a large-scale system, we propose a hierarchical Account-aided Reputation Management system (ARM) to efficiently and effectively provide cooperation incentives with small overhead. To globally collect all node reputation information to accurately calculate node reputation information and detect abnormal reputation information with low overhead, ARM builds a hierarchical locality-aware Distributed Hash Table (DHT) infrastructure for the efficient and integrated operation of both reputation systems and price systems. Based on the DHT infrastructure, ARM can reduce the reputation management overhead in reputation and price systems. We also design a distributed reputation manager auditing protocol to detect a malicious reputation manager. The experimental results show that ARM can detect the uncooperative nodes that gain fraudulent benefits while still being considered as trustworthy in previous reputation and price systems. Also, it can effectively identify misreported, falsified, and conspiratorial information, providing accurate node reputations that truly reflect node behaviors. Regarding an efficient distributed system, we propose a social network and duration utility-based distributed multi-copy routing protocol for delay tolerant networks based on the ARM system. The routing protocol fully exploits node movement patterns in the social network to increase delivery throughput and decrease delivery delay while generating low overhead. The simulation results show that the proposed routing protocol outperforms the epidemic routing and spray and wait routing in terms of higher message delivery throughput, lower message delivery delay, lower message delivery overhead, and higher packet delivery success rate. The three components proposed in this dissertation research improve the trustworthiness, scalability, and efficiency of distributed wireless systems to meet the requirements of diversified distributed wireless applications

An Incentive Mechanism for Cooperative Data Replication in MANETs - A Game Theoretical Approach

Wireless ad hoc networks have seen a great deal of attention in the past years, especially in cases where no infrastructure is available. The main goal in these networks is to provide good data accessibility for participants. Because of the wireless nodes’ continuous movement, network partitioning occurs very often. In order to subside the negative effects of this partitioning and improve data accessibility and reliability, data is replicated in nodes other than the original owner of data. This duplication costs in terms of nodes’ storage space and energy. Hence, autonomous nodes may behave selfishly in this cooperative process and do not replicate data. This kind of phenomenon is referred to as a strategic situation and is best modeled and analyzed using the game theory concept. In order to address this problem we propose a game theory data replication scheme by using the repeated game concept and prove that it is in the nodes’ best interest to cooperate fully in the replication process if our mechanism is used

A Job Market Signaling Scheme for Incentive and Trust Management in Vehicular Ad Hoc Networks

International audienceIn collaborative wireless networks with a low infrastructure, the presence of misbehaving nodes can have a negative impact on network performance. In particular, we are interested in dealing with this nasty presence in road safety applications, based on vehicular ad hoc networks (VANETs). In this work, we consider as harmful the presence of malicious nodes, which spread false and forged data; and selfish nodes, which cooperate only for their own benefit. To deal with this, we propose a Distributed Trust Model (DTM2), adapted from the job market signaling model. DTM2 is based on allocating credits to nodes and securely managing these credits. To motivate selfish nodes to cooperate more, our solution establishes the cost of reception to access data, forcing them to earn credits. Moreover, to detect and exclude malicious nodes, DTM2 requires the cost of sending, using signaling values inspired form economics and based on the node's behavior, so that the more a node is malicious, the higher its sending cost, thus limiting their participation in the network. Similarly, rewards are given to nodes whose sent messages are considered as truthful, and that paid a sending cost considered as correct. The latter is a guarantee for the receivers about the truthfulness of the message since, in case of message refusal, the source node is not rewarded despite its payment. We validated DTM2 via a theoretical study using Markov chains; and with a set of simulations, in both urban and highway scenarios. Both theoretical and simulation results show that DTM2 excludes from the network 100% of malicious nodes, without causing any false positive detection. Moreover, our solution guarantees a good ratio of reception even in the presence of selfish nodes

A novel multi-agent and multilayered game formulation for Intrusion Detection in Internet of Things (IoT)

The current era of smart computing and enabling technologies encompasses the Internet of Things (IoT) as a network of connected, intelligent objects where objects range from sensors to smartphones and wearables. Here, nodes or objects cooperate during communication scenarios to accomplish effective throughput performance. Despite the deployment of large-scale infrastructure-based communications with faster access technologies, IoT communication layers can still be affected with security vulnerabilities if nodes/objects do not cooperate and intend to take advantage of other nodes for fulfilling their malevolent interest. Therefore, it is essential to formulate an intrusion detection/prevention system that can effectively identify the malicious node and restrict it from further communication activities—thus, the throughput, and energy performance can be maximized to a significant extent. This study introduces a combined multi-agent and multilayered game formulation where it incorporates a trust model to assess each node/object, which is participating in IoT communications from a security perspective. The experimental test scenarios are numerically evaluated, where it is observed that the proposed approach attains significantly improves intrusion detection accuracy, delay, and throughput performance as compared to the existing baseline approaches

Reputation based selfishness prevention techniques for mobile ad-hoc networks

Mobile ad-hoc networks require nodes to cooperate in the relaying of data from source to destination. However, due to their limited resources, selfish nodes may be unwilling to forward packets, which can deteriorate the multi-hop connectivity. Different reputation-based protocols have been proposed to cope with selfishness in mobile ad-hoc networks. These protocols utilize the watchdog detection mechanism to observe the correct relaying of packets, and to compile information about potential selfish nodes. This information is used to prevent the participation of selfish nodes in the establishment of multi-hop routes. Despite its wide use, watchdog tends to overestimate the selfish behavior of nodes due to the effects of radio transmission errors or packet collisions that can be mistaken for intentional packet drops. As a result, the availability of valid multi-hop routes is reduced, and the overall performance deteriorates. This paper proposes and evaluates three detection techniques that improve the ability of selfishness prevention protocols to detect selfish nodes and to increase the number of valid routes.Ingeniería, Industria y Construcció

Enhancing Node Cooperation in Mobile Wireless Ad Hoc Networks with Selfish Nodes

In Mobile Ad Hoc Networks (MANETs), nodes depend on each other for routing and forwarding packets. However, to save power and other resources, nodes belonging to independent authorities may behave selfishly, and may not be willing to help other nodes. Such selfish behavior poses a real threat to the proper functioning of MANETs. One way to foster node cooperation is to introduce punishment for selfish nodes. Based on neighbor-monitoring techniques, a fully distributed solution to detect, punish, and re-admit selfish nodes, is proposed here. This solution provides nodes the same opportunity to serve/and be served by others. A light-weight solution regarding battery status is also proposed here. This solution requires neighbor monitoring only when necessary, thereby saving nodes battery power. Another effective way to solve the selfish-node problem is to reward nodes for their service according to their cost. To force nodes to show their true cost, truthful protocols are needed. A low overhead truthful routing protocol to find optimal routes is proposed in this thesis. The most prominent feature of this protocol is the reduction of overhead from existing solutions O(n3) to O(n2). A light-weight scalable truthful routing protocol (LSTOP) is further proposed, which finds near-least-cost paths in dense networks. LSTOP reduces overhead to O(n) on average, and O(n2) in worst case scenarios. Multiple path routing protocols are an effective alternative to single path routing protocols. A generic mechanism that can turn any table-driven multipath routing protocol into a truthful one, is outlined here. A truthful multipath routing protocol (TMRP), based on well-known AOMDV protocol, is presented as an example. TMRP incurs an only 2n message overhead for a route discovery, and can also achieve load balancing without compromising truthfulness. To cope with the selfish-node problem in the area of position-based routing, a truthful geographic forwarding (TGF) algorithm is presented. TGF utilizes three auction-based forwarding schemes to stimulate node cooperation. The truthfulness of these schemes is proven, and their performance is evaluated through statistical analysis and simulation studies