A guided tour of P-Nut (Release 2.2)

P-NUT is a suite of tools for constructing and analyzing Petri Net models. The tools have been developed at UCI to aid researchers in applying Petri Nets to the design of concurrent hardware/software. The tools support state-space analysis, simulation, performance evaluation and verification. While the tools are useful in their current state, the P-NUT system is just beginning to achieve its overall objective of aiding in the design of complex distributed real-time systems. This report provides a guided tour of the tools for researchers who are interested in exploring P-NUT's capabilities

Conservation of Mass Analysis for Bio-PEPA

AbstractThis paper describes a static analysis for Bio-PEPA models based on the notion of conservation of mass. Failure to obey the law of mass conservation can be an indication that there is an error in the model description. Here we focus on the use of invariant analysis to identify such potential flaws in models. We extend the basic technique to consider open models, in which it is possible to automatically ignore some causes of mass production or consumption that are unlikely to be errors. Our approach is an improvement on direct application of invariant analysis because it does not depend on a deep understanding of the model and prior expectations of the sets of components which should have conserved mass. We demonstrate the use of our technique on a published model from the literature and explain how our analysis can be used to uncover potential problems in the model description. Of course, not all models which fail to conserve mass are flawed. Nevertheless, this represents an important method of model verification which can be applied before the model itself is evaluated — since the analysis does not depend on accurate dynamics it can be undertaken early in the model development process, before the model has been fully parameterised

Analyzing Interaction Patterns to Verify a Simulation/Game Model

Thesis (Ph.D.) - Indiana University, School of Education, 2012In order for simulations and games to be effective for learning, instructional designers must verify that the underlying computational models being used have an appropriate degree of fidelity to the conceptual models of their real-world counterparts. A simulation/game that provides incorrect feedback is likely to promote misunderstanding and adversely affect learning and transfer. Numerous methods for verifying the accuracy of a computational model exist, but it is generally accepted that no single method is adequate and that multiple methods should be used. The purpose of this study was to propose and test a new method for collecting and analyzing users' interaction data (e.g., choices made, actions taken, results and feedback obtained) to provide quantified evidence that the underlying computational model of a simulation/game represents the conceptual model with sufficient accuracy. In this study, analysis of patterns in time (APT) was used to compare gameplay results from the Diffusion Simulation Game (DSG) with predictions based on diffusion of innovations theory (DOI). A program was written to automatically play the DSG by analyzing the game state during each turn, seeking patterns of game component attributes that matched optimal strategies based on DOI theory. When the use of optimal strategies did not result in the desired number of successful games, here defined as the threshold of confidence for model verification, further investigation revealed flaws in the computational model. These flaws were incrementally corrected and subsequent gameplay results were analyzed until the threshold of confidence was achieved. In addition to analysis of patterns in time for model verification (APTMV), other verification methods used included code walkthrough, execution tracing, desk checking, syntax checking, and statistical analysis. The APTMV method was found to be complementary to these other methods, providing quantified evidence of the computational model's degree of accuracy and pinpointing flaws that could be corrected to improve fidelity. The APTMV approach to verification and improvement of computational models is described and compared with other methods, and improvements to the process are proposed

Using Qualitative Discrete Event Simulation to Calculate Near Exact Output Statistics

The scope of this dissertation is to develop a statistical analysis method for the Qualitative Discrete Event Simulation (QDES) methodology. The method presented shows the calculation of the probability of occurrence and the event time distribution for each event that is generated using QDES by imposing an assumption on the distribution of the delay intervals in the simulation, in particularly uniform distribution. The resulting calculations are used in calculating the simulation time-persistent output statistics and tally statistics for variables of interests. The Qualitative Discrete Event Simulation (QDES) methodology has been advanced as a decision tool and its capability has been enhanced to provide meaningful output information. A probabilistic approach to the statistical analysis of a QDES model has been developed. The advancement in the area of reasoning with probability to produce near exact output statistics from QDES will allow modelers to make wise decisions based on a single run, instead of sampling from multiple runs as in a regular discrete event simulation model. The near exact output statistics will be able to describe the distribution of different variables, such as the queue length, customer delay, server utilization, etc., together with information for the probability of these average values occurring for each variable and the event sequences that lead to these values. The probabilistic nature of our approach to calculating statistics from a QDES output opens up new chapter on creating a closed-form discrete event simulation output. The key behind the approach is that by imposing statistical distribution on the temporal intervals and using a complex set of conditional probabilities for the thread, the statistics in the QDES model is exactly represented.Industrial Engineering & Managemen

AGENT-BASED DISCRETE EVENT SIMULATION MODELING AND EVOLUTIONARY REAL-TIME DECISION MAKING FOR LARGE-SCALE SYSTEMS

Computer simulations are routines programmed to imitate detailed system operations. They are utilized to evaluate system performance and/or predict future behaviors under certain settings. In complex cases where system operations cannot be formulated explicitly by analytical models, simulations become the dominant mode of analysis as they can model systems without relying on unrealistic or limiting assumptions and represent actual systems more faithfully. Two main streams exist in current simulation research and practice: discrete event simulation and agent-based simulation. This dissertation facilitates the marriage of the two. By integrating the agent-based modeling concepts into the discrete event simulation framework, we can take advantage of and eliminate the disadvantages of both methods.Although simulation can represent complex systems realistically, it is a descriptive tool without the capability of making decisions. However, it can be complemented by incorporating optimization routines. The most challenging problem is that large-scale simulation models normally take a considerable amount of computer time to execute so that the number of solution evaluations needed by most optimization algorithms is not feasible within a reasonable time frame. This research develops a highly efficient evolutionary simulation-based decision making procedure which can be applied in real-time management situations. It basically divides the entire process time horizon into a series of small time intervals and operates simulation optimization algorithms for those small intervals separately and iteratively. This method improves computational tractability by decomposing long simulation runs; it also enhances system dynamics by incorporating changing information/data as the event unfolds. With respect to simulation optimization, this procedure solves efficient analytical models which can approximate the simulation and guide the search procedure to approach near optimality quickly.The methods of agent-based discrete event simulation modeling and evolutionary simulation-based decision making developed in this dissertation are implemented to solve a set of disaster response planning problems. This research also investigates a unique approach to validating low-probability, high-impact simulation systems based on a concrete example problem. The experimental results demonstrate the feasibility and effectiveness of our model compared to other existing systems

Оценка качества функционирования комплексных систем технической защиты и систем поддержки принятия решения в их составе

Створення складних систем, а також оцінка якості їх функціонування й працездатності передбачає розв'язання широкого кола різнопланових завдань. Причому інтенсивне застосування засобів обчислювальної техніки й автоматизації в них постійно коректує погляди на діяльність цих систем, до складу яких входять також і системи підтримки ухвалення рішення. Підвищення якості й скорочення часу прийняття рішень при керуванні складними системами різного призначення наразі неможливе без розробки ефективних програмних і апаратних засобів, що забезпечують діяльність обслуговуючого персоналу. Особливо гостро стоїть ця проблема при прийнятті рішень (ПР) у комплексних системах технічного захисту (КСТЗ), що працюють у реальному часі, де дефіцит часу відчувається особливо сильно, а наслідки при несвоєчасному або неправильному ухваленні рішення можуть бути катастрофічними. У зв'язку із цим і з'явилася необхідність у застосуванні систем підтримки прийняття рішень (СППР), основним завданням яких є надання допомоги фахівцям у процесі прийняття раціонального й оптимального рішення в складних ситуаціях, що виникають при функціонуванні КСТЗ у реальному часі. Причому оцінка якості вибору рішень і їх параметрів повинні здійснюватися на базі моделей, які дозволили б оцінювати застосування однієї й тієї ж системи в різних умовах експлуатації. Підвищення ефективності математичного моделювання КСТЗ можна забезпечити за рахунок моделювання, як комплексної системи, так і підсистем, які входять до її складу. Ця необхідність стимулює розробку моделей і алгоритмів, що допускають вирішення складних завдань керування системою. Тому синтез КСТЗ і СППР для них, створених на основі засобів обчислювальної техніки, повинен здійснюватися відповідно до відомих критеріїв: мікропрограмне керування; модульність побудови; магістральний обмін інформацією; можливість нарощування обчислювальної потужності. Розробка й дослідження математичних моделей КСТЗ і СППР вимагає значних часових витрат. Тому застосування мереж Петрі (МП) для таких цілей прискорює процес розв'язання цих задач. Метою роботи є розгляд можливості застосування МП для оцінки технічного стану КСТЗ і СППР, а також оцінка якості їх функціонування в різних умовах експлуатації. За своїм призначенням, структурі й виконуваним функціям СППР є невід'ємною складовою частиною КСТЗ реального часу. Тому питання синтезу СППР слід розглядати з урахуванням взаємодії алгоритмів роботи СППР із алгоритмами функціонування КСТЗ. Для сучасних систем керування КСТЗ, що працюють у реальному часі, найбільш типовою є трирівнева структура обчислювальних засобів. На першому рівні знаходиться універсальна обчислювальна машина, що має великий об'єм пам'яті; на другому – спеціалізовані ЕОМ (міні- або мікро-ЕОМ); на третьому – персональні ЕОМ у складі АРМ або керуюча об'єктом машина. Реалізація СППР у КСТЗ не змінює основних функцій обчислювальних засобів, пов'язаних з формуванням інформаційної моделі. Імітаційна модель дозволяє оцінити ефективність роботи системи й усувати конфліктні ситуації, тобто функціонування стає ситуаційним. Для оцінки ефективності функціонування СППР у складі КСТЗ необхідно змоделювати процес її роботи. Його основні цілі – уточнення технічного рішення по вибору засобів обчислювальної техніки і розподіл функцій між ними, перевірка узгодженості функціонування технічних засобів СППР, оцінка ефективності роботи СППР і КСТЗ у цілому. Таким чином, апарат МЧМП дозволяє будувати досить повні моделі функціонування алгоритмів, що відображають їхню структуру, логіку роботи й часові характеристики. Для ефективного використання широкого спектра можливостей апаратних мереж Петрі (АМП) необхідне створення на базі АМП системи спеціального математичного забезпечення з набором засобів опису, вводу, трансляції, компонування, налагодження, імітації моделі, обробки результатів моделювання й аналізу.Одним із способів досягнення компромісу між складністю й вірогідністю математичної моделі є спрощення еквівалентне об'єкту мережі, що проводиться за допомогою маршрутів функціонування системи на основі апарата нечітких відносин у просторі, обумовленому розширюваної базою ділених КСТЗ і СППР. Маршрутна модель із вірогідністю, що заздалегідь задається, дозволяє прогнозувати динаміку розвитку подій навколо КСТЗ із урахуванням СППР і їх стан. Застосування мереж Петрі для імітаційного моделювання алгоритмів роботи СППР у складі КСЗТ полягає в тому, що кожній структурній схемі алгоритму ставиться у відповідність мережа Петрі. Рух міток у ній моделює процес обчислень, виконуваних алгоритмів. Запропонований метод дозволяє прогнозувати технічний стан і функціонування КСЗТ і СППР на підставі системних оцінок з великою точністю, що дозволяє забезпечити необхідний рівень захищеності.Creating complex systems, and to assess the quality of their functioning and disability involves solving a wide range of diverse tasks. Moreover, the intensive use of computer technology and automation in them constantly corrects views on these systems, which include also the support system decision. Improving the quality and reducing the time of decision making in the management of complex systems for various purposes is currently impossible without the development of effective software and hardware that provide activities staff. Particularly acute is the problem when making decisions (MD) in complex systems technical protection (CSTP) working in real time, where the lack of time is felt particularly strongly, and consequences of untimely or incorrect decision making can be catastrophic. In this regard, and there is a need in the application of decision support systems (DSS), whose main task is to assist professionals in making rational and optimal solutions to complex situations that arise in the operation CSTP in real time. Moreover, the quality assessment of choice making and their parameters must be based on models that would assess the application of the same system in different conditions. Improving mathematical modeling CSTP can be achieved through simulation of complex systems and subsystems that make up its membership. This agreement encourages the development of models and algorithms that allow solving complex management tasks system. Therefore synthesis CSTP and DSS for them, based on computer technology, must be carried out according to known criteria: firmware control, modular construction; trunk exchange of information, the ability to increase processing power. Development and study of mathematical models CSTP and DSS requires significant time and resources. Therefore, the use of Petri nets (PN) for such purposes accelerates the resolution of these problems. The aim of the work is to examine the possibility of using IM to evaluate the technical condition CSTP and DSS, and assessing the quality of their operation in different operating conditions. According to the purpose, structure and Duties DSS is an integral part KSTZ real time. Therefore, the question of synthesis DSS should be considered with regard to interaction with the DSS algorithms algorithms functioning CSTP. For modern control systems CSTP working in real time, the most typical is a three-tier structure of computational tools. On the first level there is a universal computer that has a large amount of memory in a second - specialized computers (mini-or micro - computers) on the third - personal computers in the ECM or control object machine. Implementation of DSS in CSTP does not change the basic functions of computational tools associated with the formation of the information model. A simulation model to evaluate the effectiveness of the system and eliminate conflicts, ie, the operation becomes situational.Создание сложных систем, а также оценка качества их функционирования и работоспособности предусматривает решение широкого круга разноплановых задач. Причем интенсивное применение средств вычислительной техники и автоматизации в них постоянно корректирует взгляды на деятельность этих систем, в состав которых входят и системы поддержки принятия решения. Повышение качества и сокращение времени принятия решений при управлении сложными системами различного назначения пока невозможно без разработки эффективных программных и аппаратных средств, обеспечивающих деятельность обслуживающего персонала. Особенно остро стоит эта проблема при принятии решений (ПР) в комплексных системах технической защиты (КСТЗ), работающих в реальном времени, где дефицит времени ощущается особенно сильно, а последствия при несвоевременном или неправильном принятии решения могут быть катастрофическими. В связи с этим и появилась необходимость в применении систем поддержки принятия решений (СППР), основной задачей которых является оказание помощи специалистам в процессе принятия рационального и оптимального решения в сложных ситуациях, возникающих при функционировании КСТЗ в реальном времени. Причем оценка качества выбора решений и их параметров должны осуществляться на базе моделей, которые позволили бы оценивать применение одной и той же системы в различных условиях эксплуатации. Повышение эффективности математического моделирования КСТЗ можно обеспечить за счет моделирования, как комплексной системы, так и подсистем, входящих в ее состав. Эта необходимость стимулирует разработку моделей и алгоритмов, допускающих решения сложных задач управления системой. Поэтому синтез КСТЗ и СППР для них, созданных на основе средств вычислительной техники, должен осуществляться согласно известным критериям: микропрограммное управление; модульность построения; магистральный обмен информацией, возможность наращивания вычислительной мощности. Разработка и исследование математических моделей КСТЗ и СППР требует значительных временных затрат. Поэтому применение сетей Петри (СП) для таких целей ускоряет процесс решения этих задач. Целью работы является рассмотрение возможности применения СП для оценки технического состояния КСТЗ и СППР, а также оценка качества их функционирования в различных условиях эксплуатации. По своему назначению, структуре и выполняемым функциям СППР является неотъемлемой составной частью КСТЗ реального времени. Поэтому вопросы синтеза СППР следует рассматривать с учетом взаимодействия алгоритмов работы СППР с алгоритмами функционирования КСТЗ. Для современных систем управления КСТЗ, работающих в реальном времени, наиболее типичной является трехуровневая структура вычислительных средств. На первом уровне находится универсальная вычислительная машина, имеющая большой объем памяти, на втором - специализированные ЭВМ (мини-или микро-ЭВМ), на третьем - персональные ЭВМ в составе АРМ или управляющая объектом машина. Реализация СППР в КСТЗ не меняет основных функций вычислительных средств, связанных с формированием информационной модели. Имитационная модель позволяет оценить эффективность работы системы и устранять конфликтные ситуации, т.е. функционирование становится ситуационным. Для оценки эффективности функционирования СППР в составе КСТЗ необходимо смоделировать процесс ее работы. Его основные цели - уточнение технического решения по выбору средств вычислительной техники и распределение функций между ними, проверка согласованности функционирования технических средств СППР, оценка эффективности работы СППР и КСТЗ в целом. Таким образом, аппарат МЧМП позволяет строить достаточно полные модели функционирования алгоритмов, отражающих их структуру, логику работы и временные характеристики. Для эффективного использования широкого спектра возможностей аппаратных СП (АСП) необходимо создание на базе АСП системы специального математического обеспечения с набором средств описания, ввода трансляции, компоновки, наладки, имитации модели, обработки результатов моделирования и анализа. Одним из способов достижения компромисса между сложностью и вероятностью математической модели является эквивалентное объекту сети упрощение, которое производится с помощью маршрутов функционирования системы на основе аппарата нечетких отношений в пространстве, определяемом расширяемой базой деленных КСТЗ и СППР. Маршрутная модель с предварительно задаваемой вероятностью, позволяет прогнозировать динамику развития событий вокруг КСТЗ с учетом СППР и их состояние. Применение СП для имитационного моделирования алгоритмов работы СППР в составе КСЗТ заключается в том, что каждой структурной схеме алгоритма ставится в соответствие СП. Движение меток в ней моделирует процесс вычислений, выполняемых алгоритмов. Предложенный метод позволяет прогнозировать техническое состояние и функционирование КСЗТ и СППР на основании системных оценок с большой точностью, что позволяет обеспечить необходимый уровень защищенности. To evaluate the effectiveness of DSS in the CSTP to simulate the process of work. Its main goals - clarifying technical solution on the choice of computer technology and the distribution of functions between them, checking consistency of functioning hardware DSS, evaluation of DSS and CSTP in general. Thus, the device allows you to build MCHMP fairly complete model of the algorithms that reflect their structure, logic and temporal characteristics. For efficient use of a wide range of hardware capabilities of Petri nets (HPN) required the establishment of a special HPN system of software with a set of descriptions, input translation, layout, debugging, simulation models, process simulation results and analysis. One way to achieve a compromise between complexity and reliability of the mathematical model is simplified equivalent network facilities, conducted by route of the system based on fuzzy relations in space, caused expandable base dividend CSTP and DSS. Route model of the probability that the advance is given, allows to predict the dynamics of the events surrounding CSTP taking into account the DSS and their condition. The use of Petri nets for simulation algorithms in the DSS CSTP is that each block diagram of the algorithm is associated with Petri nets. Movement marks it simulates the process of calculations performed by algorithms. The proposed method allows to predict the technical condition and operation CSTP and DSS based on systematic evaluations with high accuracy, which ensures the necessary level of security

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

Design and Performance Analysis of Opportunistic Routing Protocols for Delay Tolerant Networks

Delay Tolerant Networks (DTNs) are characterized by the lack of continuous end-to-end connections because of node mobility, constrained power sources, and limited data storage space of some or all of its nodes. Applications of DTNs include vehicular networks and sensor networks in suburban and rural areas. The intermittent connection in DTNs creates a new and challenging environment that has not been tackled before in wireless and wired networks. Traditional routing protocols fail to deliver data packets because they assume the existence of continuous end-to-end connections. To overcome the frequent disconnections, a DTN node is required to store data packets for long periods of time until it becomes in the communication range of other nodes. In addition, to increase the delivery probability, a DTN node spreads multiple copies of the same packet on the network so that one of the copies reaches the destination. Given the limited storage and energy resources of DTN nodes, there is a trade off between maximizing delivery and minimizing storage and energy consumption. DTN routing protocols can be classified as either blind routing, in which no information is provided to select the next node in the path, or guided routing, in which some network information is used to guide data packets to their destinations. In addition they differ in the amount of overhead they impose on the network and its nodes. The objective of DTN routing protocols is to deliver as many packets as possible. Acquiring network information helps in maximizing packet delivery probability and minimizing the network overhead resulting from replicating many packet copies. Network information could be node contact times and durations, node buffer capacities, packet lifetimes, and many others. The more information acquired, the higher performance could be achieved. However, the cost of acquiring the network information in terms of delay and storage could be high to the degree that render the protocol impractical. In designing a DTN routing protocol, the trade-off between the benefits of acquiring information and its costs should be considered. In this thesis, we study the routing problem in DTN with limited resources. Our objective is to design and implement routing protocols that effectively handles the intermittent connection in DTNs to achieve high packet delivery ratios with lower delivery cost. Delivery cost is represented in terms of number of transmissions per delivered packet. Decreasing the delivery cost means less network overhead and less energy consumption per node. In order to achieve that objective, we first target the optimal results that could be achieved in an ideal scenario. We formulate a mathematical model for optimal routing, assuming the presence of a global observer that can collect information about all the nodes in the network. The optimal results provide us with bounds on the performance metrics, and show the room for improvement that should be worked on. However, optimal routing with a global observer is just a theoretical model, and cannot be implemented practically. In DTNs, there is a need for a distributed routing protocol which utilizes local and easily-collectable data. Therefore, We investigate the different types of heuristic (non-optimal) distributed routing protocols, showing their strengths and weaknesses. Out of the large collection of protocols, we select four protocols that represent different routing classes and are well-known and highly referred by others working in the same area. We implement the protocols using a DTN simulator, and compare their performance under different network and node conditions. We study the impact of changing the node buffer capacities, packet lifetimes, number of nodes, and traffic load on their performance metrics, which are the delivery ratio, delivery cost, and packet average delay. Based on these comparisons, we draw conclusions and guidelines to design an efficient DTN routing protocol. Given the protocol design guidelines, we develop our first DTN routing protocol, Eco-Friendly Routing for DTN (EFR-DTN), which combines the strengths of two of the previously proposed protocols to provide better delivery ratio with low network overhead (less power consumption). The protocol utilizes node encounters to estimate the route to destination, while minimizing the number of packet copies throughout the network. All current DTN routing protocols strive to estimate the route from source to destination, which requires collecting information about node encounters. In addition to the overhead it imposes on the network to collect this information, the time to collect this information could render the data worthless to propagate through the network. Our next proposal is a routing protocol, Social Groups Based Routing (SGBR), which uses social relations among network nodes to exclude the nodes that are not expected to significantly increase the probability of delivering the packet to its destination. Using social relations among nodes, detected from node encounters, every group of nodes can form a social group. Nodes belonging to the same social group are expected to meet each other frequently, and meet nodes from other groups less frequently. Spreading packet copies inside the same social group is found to be of low-added value to the carrying node in delivering a packet to its destination. Therefore, our proposed routing protocol spreads the packet copies to other social groups, which decreases the number of copies throughout the network. We compare the new protocol with the optimal results and the existing well-known routing protocols using real-life simulations. Results show that the proposed protocol achieves higher delivery ratio and less average delay compared to other protocols with significant reduction in network overhead. Finally, we discuss the willingness of DTN nodes to cooperate in routing services. From a network perspective, all nodes are required to participate in delivering packets of each other. From a node perspective, minimizing resource consumption is a critical requirement. We investigate the degree of fair cooperation where all nodes are satisfied with their participation in the network routing services. A new credit-based system is implemented to keep track of and reward node participation in packet routing. Results show that the proposed system improves the fairness among nodes and increases their satisfaction