This document describes the Optimized Link State Routing (OLSR) protocol for mobile ad hoc networks. The protocol is an optimization of the classical link state algorithm tailored to the requirements of a mobile wireless LAN. The key concept used in the protocol is that of multipoint relays (MPRs). MPRs are selected nodes which forward broadcast messages during the flooding process. This technique substantially reduces the message overhead as compared to a classical flooding mechanism, where every node retransmits each message when it receives the first copy of the message. In OLSR, link state information is generated only by nodes elected as MPRs. Thus, a second optimization is achieved by minimizing the number of control messages flooded in the network. As a third optimization, an MPR node may chose to report only links between itself and its MPR selectors. Hence, as contrary to the classic link state algorithm, partial link state information is distributed in the network. This information is then used for route calculation. OLSR provides optimal routes (in terms of number of hops). The protocol is particularly suitable for large and dense networks as the technique of MPRs works well in this context.

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Optimized Link State Routing Protocol (OLSR)

Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

System Identification I

In this paper we propose and discuss an optimized link state routing protocol, named OLSR, for mobile wireless networks. The protocol is based on the link state algorithm and it is proactive (or table-driven) in nature. It employs periodic exchange of messages to maintain topology information of the network at each node. OLSR is an optimization over a pure link state protocol as it compacts the size of information sent in the messages, and furthermore, reduces the number of retransmissions to flood these messages in an entire network. For this purpose, the protocol uses the multipoint relaying technique to efficiently and economically flood its control messages. It provides optimal routes in terms of number of hops, which are immediately available when needed. The proposed protocol is best suitable for large and dense ad hoc networks.

/pdf/optimized-link-state-routing-protocol-for-ad-hoc-networks-1hwadgendm.pdf

Optimized link state routing protocol for ad hoc networks

Power Aware Routing in Mobile Ad Hoc Networks

In this paper, we present an industrial development of a wireless sensor network technology called OCARI: optimization of communication for ad hoc reliable industrial networks. It targets applications in harsh environments such as power plants and warships. OCARI is a wireless-communication technology that supports mesh topology and power-aware ad hoc routing protocol aimed at maximizing the network lifetime. It is based on IEEE 802.15.4 physical layer with deterministic media access control layer for time-constrained communication. During the nontime-constrained communication period, its ad hoc routing strategy uses an energy-aware optimized-link state-routing proactive protocol. An OCARI application layer (APL) is based on ZigBee application support sublayer and APL primitives and profiles to provide maximum compatibility with ZigBee applications. To fully assess this technology, extensive tests are done in industrial facilities at ElectricitEacute De France R&D as well as at Direction des Constructions Navales Services. Our objective is then to promote this specification as an open standard of industrial wireless technology.

Which Wireless Technology for Industrial Wireless Sensor Networks? The Development of OCARI Technology

The myriad of potential applications supported by wireless sensor networks (WSNs) has generated much interest from the research community. Various applications range from small size low industrial monitoring to large scale energy constrained environmental monitoring. In all cases, an operational network is required to fulfill the application missions. In addition, energy consumption of nodes is a great challenge in order to maximize network lifetime. Unlike other networks, it can be hazardous, very expensive or even impossible to charge or replace exhausted batteries due to the hostile nature of environment. Researchers are invited to design energy efficient protocols while achieving the desired network operations. This paper focuses on different techniques to reduce the consumption of the limited energy budget of sensor nodes. After having identified the reasons of energy waste in WSNs, we classify energy efficient techniques into five classes, namely data reduction, control reduction, energy efficient routing, duty cycling and topology control. We then detail each of them, presenting subdivisions and giving many examples. We conclude by a recapitulative table.

/pdf/a-survey-on-energy-efficient-techniques-in-wireless-sensor-49guq9acg0.pdf

A survey on energy efficient techniques in wireless sensor networks

We analyze the performance of ad hoc pro-active routing protocols. In particular we focuse on the multipoint relay concept introduced in OLSR protocol and which brings a significantimpro vementin broadcast control traffic overhead. We analyze the performance in two radio network model: the random graph model and the unit graph model. The random graph is more suitable for the modelization of indoor networks. The unit graph is more suitable for outdoor networks. We compare the performance of OLSR with the performance of basic link state protocols using full flooding.

/pdf/performance-of-multipoint-relaying-in-ad-hoc-mobile-routing-18u05jmdpj.pdf

Performance of Multipoint Relaying in Ad Hoc Mobile Routing Protocols

The diversity of the applications supported by wireless ad hoc and sensor networks explain the success of these networks. However, their energy constrained nature requires the use of energy efficient strategies to maximize network lifetime. We can classify these strategies in four categories: 1. energy efficient routing, 2. scheduling the nodes sleeping state, 3. topology control by tuning node transmission power and 4. reducing the volume of information transferred. For each category, a state of the art is given and new protocols are presented. The best energy efficiency will be obtained by combining all the four categories of strategies. A cross-layering approach is a promising tradeoff between generic solutions and solutions optimized for a specific application.

Survey of Energy Efficient Strategies in Wireless Ad Hoc and Sensor Networks

With the current increase in ad-hoc mobile networks in public domains (e.g. airports, cities, etc.), and the widespread use of IEEE 802.11 wireless LAN, there is a growing need to handle and manage fast mobility. Extending the coverage area of ad-hoc networks and taking into account fast mobility in routing protocols could offer a complementary solution to the UMTS for fourth generation (4G) mobile networks. In this paper we present an extension of the optimized link state routing protocol (OLSR), denoted Fast-OLSR, which is designed to meet the need for fast mobility in mobile ad-hoc networks (MANETs). Performance evaluation of Fast-OLSR is done by simulation, and the results show that the loss rate can be minimized while maintaining a reasonable overhead traffic.

/pdf/integrating-fast-mobility-in-the-olsr-routing-protocol-1ubzi85yz9.pdf

Pascale Minet

Papers

Which Wireless Technology for Industrial Wireless Sensor Networks? The Development of OCARI Technology

A survey on energy efficient techniques in wireless sensor networks

Performance of Multipoint Relaying in Ad Hoc Mobile Routing Protocols

Survey of Energy Efficient Strategies in Wireless Ad Hoc and Sensor Networks

Integrating fast mobility in the OLSR routing protocol