The main principle behind the working of delay tolerant networks (DTN) is the mobility of the nodes along with their contact sequences for exchanging data. Nodes which are a part of the DTN network can behave selfishly due to network reservation policy, especially when constrained to energy or storage space. Several forwarding protocols exist for spreading data but our focus is on the performance of popular data relaying protocols namely epidemic routing and two hop routing protocol in a situation where nodes exhibit various degrees of selfishness. Results of an analytical model show the performance advantage of epidemic routing over two hop routing decreases as the number of selfish nodes and intensity of the selfishness increases either deterministically or probabilistically. We practically asses the vulnerability of the above mentioned protocols using ONE simulator. We find that our result coincides with analytical results with some variations in the graph.

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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.

Large--scale distributed environments can be seen as a conflict between the selfish aims of the participants and the group welfare of the population as a whole. In order to regulate the behavior of the participants it is often necessary to introduce mechanisms that provide incentives and stimulate cooperative behavior in order to mitigate for the resultant potentially undesirable availability outcomes which could arise from individual actions.The history of economics contains a wide variety of incentive patterns for cooperation. In this thesis, we adopt bartering incentive pattern as an attractive foundation for a simple and robust form of exchange to re-allocate resources. While bartering is arguably the world's oldest form of trade, there are still many instances where it surprises us. The success and survivability of the barter mechanisms adds to its attractiveness as a model to study.In this thesis we have derived three relevant scenarios where a bartering approach is applied. Starting from a common model of bartering: - We show the price to be paid for dealing with selfish agents in a bartering environment, as well as the impact on performance parameters such as topology and disclosed information.- We show how agents, by means of bartering, can achieve gains in goods without altruistic agents needing to be present.- We apply a bartering--based approach to a real application, the directory services.The core of this research is the analysis of bartering in the Internet Age. In previous times, usually economies dominated by bartering have suffered from high transaction costs (i.e. the improbability of the wants, needs that cause a transaction occurring at the same time and place). Nowadays, the world has a global system of interconnected computer networks called Internet. This interconnected world has the ability to overcome many challenges of the previous times. This thesis analysis the oldest system of trade within the context of this new paradigm. In this thesis we aim is to show thatbartering has a great potential, but there are many challenges that can affect the realistic application of bartering that should be studied.The purpose of this thesis has been to investigate resource allocation using bartering mechanism, with particular emphasis on applications in largescale distributed systems without the presence of altruistic participants in the environment.Throughout the research presented in this thesis we have contributed evidence that supports the leitmotif that best summarizes our work: investigation interactions amongst selfish, rational, and autonomous agents with incomplete information, each seeking to maximize its expected utility by means of bartering. We concentrate on three scenarios: one theoretical, a case of use, and finally a real application. All of these scenarios are used for evaluating bartering. Each scenario starts from a common origin, but each of them have their own unique features.The final conclusion is that bartering is still relevant in the modern world.

In wireless packet-forwarding networks, the nodes or users are always selfish to maximize their utilities in nature. Selfish users would not like to help others for forward each others¡¦ packets, which will cause the network performance degrades severely. To solve the packet-forwarding problem, we propose a novel coalitional game approach based orthogonal decode-and-forward (ODF) relaying scheme to encourage the selfish users for cooperation. In the game-theoretic analysis, we study the properties and stability of the coalitions thoroughly. Furthermore, we prove that the cohesive behavior can be obtained by the aspect of outage probability indeed in this game. Simulation results show that the proposed ODF coalitional game can enforce cooperation exactly and it is always beneficial to form the cooperative groups for all users.

abstract: While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by many individual entities. These entities make their decisions independently and selfishly, and maybe cooperate with a small group of other entities only when this form of coalition yields a better return. The interaction among multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives. In this dissertation, we are interested in modeling, analyzing, addressing network problems caused by the selfish behavior of network entities. First, we study how the selfish behavior of network entities affects the system performance while users are competing for limited resource. For this resource allocation domain, we aim to study the selfish routing problem in networks with fair queuing on links, the relay assignment problem in cooperative networks, and the channel allocation problem in wireless networks. Another important aspect of this dissertation is the study of designing efficient mechanisms to incentivize network entities to achieve certain system objective. For this incentive mechanism domain, we aim to motivate wireless devices to serve as relays for cooperative communication, and to recruit smartphones for crowdsourcing. In addition, we apply different game theoretic approaches to problems in security and privacy domain. For this domain, we aim to analyze how a user could defend against a smart jammer, who can quickly learn about the user's transmission power. We also design mechanisms to encourage mobile phone users to participate in location privacy protection, in order to achieve k-anonymity. / Dissertation/Thesis / Ph.D. Computer Science 2013

Selfish genetic elements break the rules of Mendelian inheritance to bias their transmission to following generations, often with negative fitness consequences. A striking example involves selfish X chromosomes that operate in males and interfere with the production of sperm that carry a Y chromosome. Only X chromosome-bearing sperm are produced, and this can result in extraordinary female-biased sex-ratio distortions. Most studies have focused on how selfish X chromosomes operate in and affect males, and there has been relatively little work on their consequences in females. In this thesis, I characterize fitness effects and transmission in females, in a recently discovered selfish X chromosome system in Drosophila testacea, a common woodland fly. I show that females with two copies of the selfish X chromosome have reduced fitness compared to females carrying zero, or one copy. Specifically, these females have a lower hatch rate and lifetime fecundity. Additionally, I show that heterozygous females are more likely to transmit the selfish X chromosome than the wildtype copy to their offspring. I observe this transmission bias in eggs, larvae, and adults, which suggests that the selfish X chromosome is preferentially segregating into the egg, rather than the polar bodies, during oogenesis. We believe this is the first documented case of a selfish X chromosome acting through both sexes. The negative fitness effects and the biased transmission in males and females will have important consequences on the evolutionary dynamics of the selfish X chromosome. In addition, the phenomenon of biased transmission in both sexes has the potential to yield interesting insights in the mechanism of meiotic drive. / Graduate / 2022-05-12

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This dissertation focuses on robust coalition formation between selfish agents in a dynamic environment where contracts are unenforceable. Previous research on this topic has covered each different aspect of this problem, but no research successfully addresses these factors in combination. Therefore, a novel approach is required. This dissertation accordingly has three major goals: to develop a theoretical framework that describes how selfish agents should select jobs and partners in a dynamic, contractless environment, to test a strategy based on that framework against existing heuristics in a simulated environment, and to create a learning agent capable of optimally adjusting its coalition formation strategy based on the level of dynamic change found in its environment. Experimental results demonstrate that the Expected Utility (EU) strategy based on the developed theoretical framework performs better than strategies using heuristics to select jobs and partners, and strategies which simulate a centralized “manager”. Future work in this area includes altering the EU strategy from an anytime strategy to a hill-climbing one, as well as further game theoretic explorations of the interactions between different strategies. / text

Self-stabilizing system is a concept of fault-tolerance in distributed computing. A distributed algorithm is self-stabilizing if, starting from an arbitrary state, it is guaranteed to converge to a legal state in a finite number of states and remains in a legal set of states thereafter. The property of self-stabilization enables a distributed algorithm to recover from a transient fault regardless of its objective. Moreover, a self-stabilizing algorithm does not have to be initialized as it eventually starts to behave correctly. In this thesis, we focus on extensions and refinements of self-stabilization by studying two non-traditional aspects of self-stabilization. In traditional self-stabilizing distributed systems [13], the inherent assumption is that all processes run predefined programs mandated by an external agency which is the owner or the administrator of the entire system. The model works fine for solving problems when processes cooperate with one another, with a global goal. In modern times it is quite common to have a distributed system spanning over multiple administrative domains, and processes have selfish motives to optimize their own pay- off. Maximizing individual payoffs under the umbrella of stabilization characterizes the notion of selfish stabilization . We investigate the impact of selfishness on the existence and the complexity of stabilizing solutions to specific problems in this thesis. Our model of selfishness centers on a graph where the set of nodes is divided into subsets of distinct colors, each having their own unique perception of the edge costs. We study the problems of constructing a rooted shortest path tree and a maximum flow tree on this model, and demonstrate that when processes are selfish, there is no guarantee that a solution will exist. We demonstrate that the complexity of determining the existence of a stabilizing solution is NP-complete, carefully characterize a fraction of such cases, and propose the construction of stabilizing solutions wherever such solutions are feasible. Fault containment and system availability are important issues in today's distributed systems. In this thesis, we show how fault-containment can be added to weakly stabilizing distributed systems. We present solutions using a randomized scheduler, and illustrate techniques to bias the random schedules so that the system recovers from all single faults in a time independent of the size of the system, and the effect of the failure is contained within constant distance from the faulty node with high probability (this probability can be controlled by a user defined tuning parameter). Using this technique, we solve two problems: one is the persistent-bit problem, and the other is the leader election problem.