Optimal Cooperative Strategy Research Articles

Cooperative strategies of wireless access technologies: A game-theoretic analysis

The wireless Internet has to overcome the problem of spectrum scarcity as the number of mobile equipments could increase even by an order of magnitude in the next decade; the cooperation of mobile devices is foreseeable as a feasible solution to the problems. There exists a large body of literature on opportunistic ad hoc networking including Pelusi et al. (2006) [25], Chen et al. (2006) [26], Hui et al. (2005) [27]; however, the impact of the location of the devices on their access method selection is not yet appropriately dealt with. In this paper, we address this issue based on game-theoretic analyses. The key contribution of our work is threefold. First, we model the access method selection of mobile devices by extending the classical forwarding game with position, mobility, and availability of the devices. Second, we apply the model in game-theoretic analyses to better understand the optimal cooperation strategies in the presence of heterogeneous wireless technologies. We further extend our framework to include uncertainty. Finally, we present the applicability of the model in a cognitive radio scenario where complex structures of parameters are included.

Optimal Cooperative Relaying Schemes in IR-UWB Networks

Cooperation between wireless nodes to retransmit data for the other users introduces multiuser diversity to a wireless network and increases the system throughput. In this paper, the optimal cooperative relaying strategies in the MAC layer are analyzed while considering the UWB unique properties such as fine ranging and immunity to small scale fading. Specifically, the optimal cooperation strategies in the absence of coordination message passing between relays are determined in order to maximize the system throughput while reducing the control packet overhead. Mobile networks are also considered, in which the relays should exchange their ranging information together in some update intervals. The optimal update interval length is calculated in order to maximize the system throughput. More importantly, we show that if this optimal update interval is used, the optimal cooperation strategies in the mobile case will be similar to those in the static network. Two different relay selection schemes, namely proactive and reactive settings, are considered. Analysis and simulations confirm that the proposed UWB-based Cooperative Relaying Scheme, UCoRS, can achieve a considerable diversity gain in spite of its implementation simplicity. UCoRS also minimizes the number of control packets that are required for the optimal cooperation, which leads to the energy efficiency in the UWB costly data-receiving process.

Cooperative Profit Sharing in Coalition-Based Resource Allocation in Wireless Networks

We consider a network in which several service providers offer wireless access to their respective subscribed customers through potentially multihop routes. If providers cooperate by jointly deploying and pooling their resources, such as spectrum and infrastructure (e.g., base stations) and agree to serve each others' customers, their aggregate payoffs, and individual shares, may substantially increase through opportunistic utilization of resources. The potential of such cooperation can, however, be realized only if each provider intelligently determines with whom it would cooperate, when it would cooperate, and how it would deploy and share its resources during such cooperation. Also, developing a rational basis for sharing the aggregate payoffs is imperative for the stability of the coalitions. We model such cooperation using the theory of transferable payoff coalitional games. We show that the optimum cooperation strategy, which involves the acquisition, deployment, and allocation of the channels and base stations (to customers), can be computed as the solution of a concave or an integer optimization. We next show that the grand coalition is stable in many different settings, i.e., if all providers cooperate, there is always an operating point that maximizes the providers' aggregate payoff, while offering each a share that removes any incentive to split from the coalition. The optimal cooperation strategy and the stabilizing payoff shares can be obtained in polynomial time by respectively solving the primals and the duals of the above optimizations, using distributed computations and limited exchange of confidential information among the providers. Numerical evaluations reveal that cooperation substantially enhances individual providers' payoffs under the optimal cooperation strategy and several different payoff sharing rules.

Coordinating advertising and pricing in a manufacturer–retailer channel

Abstract Cooperative advertising is a practice that a manufacturer pays retailers a portion of the local advertising cost in order to induce sales. Cooperative advertising plays a significant role in marketing programs of channel members. Nevertheless, most studies to date on cooperative advertising have assumed that the market demand is only influenced by advertising expenditures but not by retail price. This paper addresses channel coordination by seeking optimal cooperative advertising strategies and equilibrium pricing in a two-member distribution channel. We establish and compare two models: a non-cooperative, leader–follower game and a cooperative game. We develop propositions and insights from the comparison of these models. The cooperative model achieves better coordination by generating higher channel-wide profits than the non-cooperative model with these features: (a) the retailer price is lower to consumers; and (b) the advertising efforts are higher for all channel members. We identify the feasible solutions to a bargaining problem where the channel members can determine how to divide the extra profits.

Automated self-assembly programming paradigm: The impact of network topology

In our previous work Li et al., in Proc of 3rd IEEE Int Workshop on Engineering of Automatic & Automation Systems, Potsdam, Germany, 2006, pp 25–34; Li et al., in Proc Workshop on Nature Inspired Cooperative Strategies for Optimization, Granada, Spain, 2006, pp 123–134, we introduced automated self-assembly programming paradigm (ASAP2) using unguided self-assembly and swarm-inspired methodologies. We investigated how external environment settings affect software self-assembly speed and diversity of the generated programs. In this paper, we extend our previous work with a diversified compartments approach based on general graphs. This diversified compartments approach is integrated into a network structure such that each compartment can be seen as a node in the network. We investigate how structures of the network impacts on software self-assembly speed, complexity, and diversity of generated programs. Results indicate that network structure can substantially affect the dynamics, diversity, and complexity of generated programs. © 2009 Wiley Periodicals, Inc.

Nature-inspired cooperative strategies for optimization

Nature-inspired cooperative strategies for optimization

The game to play: expanding the co‐opetition proposal through the strategic games matrix

PurposeUsing Brandenburger and Nalebuff's 1995 co‐opetition model as a reference, the purpose of this paper is to seek to develop a tool that, based on the tenets of classical game theory, would enable scholars and managers to identify which games may be played in response to the different conflict of interest situations faced by companies in their business environments.Design/methodology/approachThe literature on game theory and business strategy are reviewed and a conceptual model, the strategic games matrix (SGM), is developed. Two novel games are described and modeled.FindingsThe co‐opetition model is not sufficient to realistically represent most of the conflict of interest situations faced by companies. It seeks to address this problem through development of the SGM, which expands upon Brandenburger and Nalebuff's model by providing a broader perspective, through incorporation of an additional dimension (power ratio between players) and three novel, respectively, (rival, individualistic, and associative).Practical implicationsThis proposed model, based on the concepts of game theory, should be used to train decision‐ and policy‐makers to better understand, interpret and formulate conflict management strategies.Originality/valueA practical and original tool to use game models in conflict of interest situations is generated. Basic classical games, such as Nash, Stackelberg, Pareto, and Minimax, are mapped on the SGM to suggest in which situations they could be useful. Two innovative games are described to fit four different types of conflict situations that so far have no corresponding game in the literature. A test application of the SGM to a classic Intel Corporation strategic management case, in the complex personal computer industry, shows that the proposed method is able to describe, to interpret, to analyze, and to prescribe optimal competitive and/or cooperative strategies for each conflict of interest situation.

Rate bounds for MIMO relay channels

This paper considers the multi-input multi-output (MIMO) relay channel where multiple antennas are employed by each terminal. Compared to single-input single-output (SISO) relay channels, MIMO relay channels introduce additional degrees of freedom, making the design and analysis of optimal cooperative strategies more complex. In this paper, a partial cooperation strategy that combines transmit-side message splitting and block-Markov encoding is presented. Lower bounds on capacity that improve on a previously proposed non-cooperative lower bound are derived for Gaussian MIMO relay channels. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>

Cooperative Search with Concurrent Interactions

In this paper we show how taking advantage of autonomous agents' capability to maintain parallel interactions with others, and incorporating it into the cooperative economic search model results in a new search strategy which outperforms current strategies in use. As a framework for our analysis we use the electronic marketplace, where buyer agents have the incentive to search cooperatively. The new search technique is quite intuitive, however its analysis and the process of extracting the optimal search strategy are associated with several significant complexities. These difficulties are derived mainly from the unbounded search space and simultaneous dual affects of decisions taken along the search. We provide a comprehensive analysis of the model, highlighting, demonstrating and proving important characteristics of the optimal search strategy. Consequently, we manage to come up with an efficient modular algorithm for extracting the optimal cooperative search strategy for any given environment. A computational based comparative illustration of the system performance using the new search technique versus the traditional methods is given, emphasizing the main differences in the optimal strategy's structure and the advantage of using the proposed model.

Soft computing and cooperative strategies for optimization

In the last years, metaheuristics have emerged as powerful algorithmic approaches which have been applied with great success to difficult combinatorial optimization problems. However, this does not mean that metaheuristics can be applied blindly to any new problem. In this contribution we showed how the most basic ingredients of Soft Computing, namely fuzzy sets and fuzzy rules, are used in the context of a simple metaheuristic and a cooperative strategy based on it, to obtain successful results for the p-median problem.

A Low-Overhead Cooperative Retransmission Scheme for IR-UWB Networks

The UWB unique properties such as fine ranging and immunity to small scale fading are utilized in order to exploit the multiuser diversity in UWB networks. The optimal cooperation strategies in the absence of control packet overhead are analyzed in the proactive and reactive settings. It is shown that the proposed method achieves a considerable diversity gain while minimizing the overhead of control packet exchange that is required for coordination among the relays.

Cooperative hedging with a higher interest rate for borrowing

The paper studies the cooperative hedging problem of contingent claims in an incomplete financial market. Firstly we give the characterization of the optimal cooperative hedging strategy for the Black–Scholes model and the Volatility Jump model explicitly, then we consider the problem of cooperative hedging for the multi-agent case in a market with a higher borrowing interest rate. By the results of concave and linear backward stochastic differential equations, we give the optimal cooperative hedging strategy in our model.

Optimal cooperative advertising integration strategy for organizations adding a direct online channel

Since the advent of the Web, retailers who served consumers offline (ie in stores or via catalogue) have grappled with how to effectively integrate the Internet into their marketing strategies and tactics. Clearly, how a firm elects to integrate the Internet into its retailing process, and how it coordinates offline and online strategic decisions, can impact its performance. In this paper, we examine integration decisions from a cooperative advertising perspective to determine the profitability of various integration strategies. We find that profit is greater when using a ‘partial-integration’ strategy rather than a ‘separation’ strategy; moreover, we find that profit is yet greater when using a ‘full-integration’ strategy rather than a ‘partial-integration’ strategy.

Cooperative Hedging in Incomplete Markets

The problem of (partial) hedging contingent claims for a single agent is well studied. This paper studies the problem for the multiagent case in incomplete markets. For this case, a cooperative hedging game is posed as follows: First, all agents contribute some money and collect the money together as the initial total capital, then invest the initial total capital in a trading strategy, and, finally, divide the terminal wealth of the trading strategy and each of them gets a part. We give a characterization of the optimal cooperative hedging strategy and prove that the core of the cooperative hedging game, as a cooperative game with side payment, is nonempty.

Multi-agent investment in incomplete markets

The problem of the expected utility maximization in incomplete markets for a single agent is well understood in a fairly general setting. This paper studies the problem for the multi-agent case. For this case a cooperative investment game is posed as follows: firstly collect all agents’ capital together at the initial time, then invest the total capital in a trading strategy, and finally divide the terminal wealth of the trading strategy and each of them gets a part. We give a characterization of Pareto optimal cooperative strategies and a characterization of situations where cooperation strictly Pareto dominates non cooperation, and prove that the core of the cooperative investment game is non-empty under mild conditions using Scarf theorem.