Today I’ve started to read a technical book about cooperation and its application to wireless communications, a hot topic both in academy and in business:
Cooperation is known as an effective strategy in nature to achieve individual or common goals by forming cooperative groups. The authors look for applying the same cooperative strategies we can see in nature to the field of wireless communications at all levels. The cross over between nature and engineering has always been fruitful. Mimicking nature as a source of inspiration in engineering is a winner strategy. Thee book itself is written in a collaborative manner by several authors from Asia, America, and Europe :) Cooperation has already been studied by Social Sciences with well established theories and experiments. Now it’s being studied as a hot topic in many sub fields of wireless communications. Every chapter of the book is written formally as a paper.
I’ve read the first chapter, which has the following table of contents:
1. Cooperation in Nature and Wireless Communications;
Frank H. P. Fitzek and Marcos Katz.
1. Basics of Cooperation.
2. The Prisoner’s Dilemma.
3. The Iterated Prisoner’s Dilemma.
4. N–person Prisoner’s Dilemma.
5. Stimulating Cooperative Behavior.
6. Cooperation in Wireless Communication Systems.
7. Cooperative Principles in Wireless Communications: The Future.
In this chapter, examples of nature are cited as successful models of cooperation: lichens, carnivore hunting groups, Tour de France peloton and vampire bats. We can model those interactions and apply then to the field of wireless communications. Objective: maximize the QoS of the network, minimizing the complexity of the terminals, air interface and power consumption.
In this chapter, the authors put as a basic example a game: the prisoner’s dilemma, and two interesting derivatives: Iterated PD and N-person PD which are directly applicable to the wireless communication field. They cite Wilensky (2002) NetLogo PD N-Person Iterated Model for gathering further information and Robert Axelrod‘s tournaments. Here the participants are intelligent (embedded agent based) wireless terminals with long range cellular network and short range ad-hoc network capabilities. Among the strategies which use those terminals, we have Tit for Tat (TFT) and unforgiven Tit for Tat as the most rewarding (being pure cooperation, defecting and random the worst, respectively) These are game theory strategies. They give rules to be successful in an environment with multistrategy individuals.
Cooperation in Wireless Networks is first classified in communicational, operational and social. The communicational aspect is treated in the book. A further classification of this aspect is implicit (i.e ALOHA, TCP/IP flow control) or explicit. The explicit can be subdivided in macro (i.e relying in Wi-Fi networks) and micro (i.e lower link layers, Multiple Description Coding, Multicast, UMTS + WLAN, power saving)
I’ve found a connection between a set of cooperating agents trying to solve a problem (á la AI) and the set of terminals in an environment cooperating in order to communicate with each other. They both play a game, a prisoner’s dilemma game in which they use a series of strategies in order to maximize each one gain. Should these agents use AI techniques (i.e evolutionary computation) to manage its goals? To cooperate, terminals need information about the environment (i.e air interface, channel, other terminals) and should be able to decide what to do based on that information (i.e cognitive radio/communication over software defined radio)