The problem of how to achieve cooperation among rational peers in order to discourage free riding is one that has received a lot of attention in peer-to-peer computing and is still an important one. The field of game theory is applied to the task of finding solutions that will encourage cooperation while discouraging free riding. The cooperative conduct of peers is typically portrayed as a traditional version of the game known as the "Prisoners' Dilemma." It is common knowledge that if two peers engage in a situation known as the Prisoner's Dilemma more than once, collaboration can be achieved through the use of punishment. Nevertheless, this is not the case when there is only one interaction between peers. This short article demonstrates that Kantian peers prefer to cooperate and attain social welfare even when they interacted only once. This, dissuade peers from freeriding.

Federated learning (FL) is a promising privacy-preserving solution to build powerful AI models. In many FL scenarios, such as healthcare or smart city monitoring, the user’s devices may lack the required capabilities to collect suitable data, which limits their contributions to the global model. We contribute social-aware federated learning as a solution to boost the contributions of individuals by allowing outsourcing tasks to social connections. We identify key challenges and opportunities, and establish a research roadmap for the path forward. Through a user study with N = 30 participants, we study collaborative incentives for FL showing that social-aware collaborations can significantly boost the number of contributions to a global model provided that the right incentive structures are in place.

This article presents a communication-cooperation-collaboration (Three-C) based framework of social cloud that incorporates a socio-technical perspective. One might look at the variety of reported views and perspectives on the social cloud and see that it can serve as a special kind of computing paradigm. But, the overall concept of the social cloud is muddied by so many divergent perspectives discussed in the literature. Therefore, there is no clarity and unified view of the social cloud. Our effort unifies the concept of social cloud, making it easier to see its promise and offering a path towards its continued development and deployment in enterprise and academia. Further, this article discusses social cloud implications in business settings.

This paper focuses on social cloud formation, where agents are involved in a closenessbased conditional resource sharing and build their resource sharing network themselves. The objectives of this paper are: (1) to investigate the impact of agents’ decisions of link addition and deletion on their local and global resource availability, (2) to analyze spillover effects in terms of the impact of link addition between a pair of agents on others’ utility, (3) to study the role of agents’ closeness in determining what type of spillover effects these agents experience in the network, and (4) to model the choices of agents that suggest with whom they want to add links in the social cloud. The findings include the following. Firstly, agents’ decision of link addition (deletion) increases (decreases) their local resource availability. However, these observations do not hold in the case of global resource availability. Secondly, in a connected network, agents experience either positive or negative spillover effect and there is no case with no spillover effects. Agents observe no spillover effects if and only if the network is disconnected and consists of more than two components (sub-networks). Furthermore, if there is no change in the closeness of an agent (not involved in link addition) due to a newly added link, then the agent experiences negative spillover effect. Although an increase in the closeness of agents is necessary in order to experience positive spillover effects, the condition is not sufficient. By focusing on parameters such as closeness and shortest distances, we provide conditions under which agents choose to add links so as to maximise their resource availability.

What social cloud structure is likely to emerge when agents engage in closeness‐based resource‐sharing and establish their resource‐sharing network strategically? This is the central question of this research. This letter looks at how cost‐benefit trade‐offs in maintaining connections, and resource supply and demand influence network formation. The study reveals that agents prefer a sparse network over a dense one. A dense network is likely to form when demand exceeds supply, while a sparse network is likely to form when supply exceeds demand.

The idea of a social cloud has emerged as a resource sharing paradigm in a social network context. Undoubtedly, state-of-the-art social cloud systems demonstrate the potential of the social cloud acting as complementary to other computing paradigms such as the cloud, grid, peer-to-peer and volunteer computing. However, in this note, we have done a critical survey of the social cloud literature and come to the conclusion that these initial efforts fail to offer a general framework of the social cloud, also, to show the uniqueness of the social cloud. This short note reveals that there are significant differences regarding the concept of social cloud, resource definition, resource sharing and allocation mechanism, and its application and stakeholders. This study is an attempt to express a need for a general framework of the social cloud, which can incorporate various views and resource sharing setups discussed in the literature.

Social storage systems are a good alternative to existing data backup systems of local, centralized, and P2P backup. Till date, researchers have mostly focussed on either building such systems by using existing underlying social networks (exogenously built) or on studying quality of service related issues. In this paper, we look at two untouched aspects of social storage systems. One aspect involves modelling social storage as an endogenous social network, where agents themselves decide with whom they want to build data backup relation, which is more intuitive than exogenous social networks. The second aspect involves studying the stability of social storage systems, which would help reduce maintenance costs and further, help build efficient as well as contented networks. We have a four fold contribution that covers the above two aspects. We, first, model the social storage system as a strategic network formation game. We define the utility of each agent in the network under two different frameworks, one where the cost to add and maintain links is considered in the utility function and the other where budget constraints are considered. In the context of social storage and social cloud computing, these utility functions are the first of its kind, and we use them to define and analyse the social storage network game. Second, we propose the concept of bilateral stability which refines the pairwise stability concept defined by Jackson and Wolinsky (J Econ Theory 71(1):44–74, 1996), by requiring mutual consent for both addition and deletion of links, as compared to mutual consent just for link addition. Mutual consent for link deletion is especially important in the social storage setting. The notion of bilateral stability subsumes the bilateral equilibrium definition of Goyal and Vega-Redondo (J Econ Theory 137(1):460–492, 2007). Third, we prove necessary and the sufficient conditions for bilateral stability of social storage networks. For symmetric social storage networks, we prove that there exists a unique neighborhood size, independent of the number of agents (for all non-trivial cases), where no pair of agents has any incentive to increase or decrease their neighborhood size. We call this neighborhood size as the stability point. Fourth, given the number of agents and other parameters, we discuss which bilaterally stable networks would evolve and also discuss which of these stable networks are efficient—that is, stable networks with maximum sum of utilities of all agents. We also discuss ways to build contented networks, where each agent achieves the maximum possible utility.

This paper investigates the impact of link formation between a pair of agents on the resource availability of other agents (that is, externalities) in a social cloud network, a special case of endogenous sharing economy networks. Specifically, we study how the closeness between agents and the network size affect externalities. We conjecture, and experimentally support, that for an agent to experience positive externalities, an increase in its closeness is necessary. The condition is not sufficient though. We, then, show that for populated ring networks, one or more agents experience positive externalities due to an increase in the closeness of agents. Further, the initial distance between agents forming a link has a direct bearing on the number of beneficiaries, and the number of beneficiaries is always less than that of non-beneficiaries.

In this paper, we study the formation of endogenous social storage cloud in a dynamic setting, where rational agents build their data backup connections strategically. We propose a degree-distance-based utility model, which is a combination of benefit and cost functions. The benefit function of an agent captures the expected benefit that the agent obtains by placing its data on others’ storage devices, given the prevailing data loss rate in the network. The cost function of an agent captures the cost that the agent incurs to maintain links in the network. With this utility function, we analyze what network is likely to evolve when agents themselves decide with whom they want to form links and with whom they do not. Further, we analyze which networks are pairwise stable and efficient. We show that for the proposed utility function, there always exists a pairwise stable network, which is also efficient. We show that all pairwise stable networks are efficient, and hence, the price of anarchy is the best that is possible. We also study the effect of link addition and deletion between a pair of agents on their, and others’, closeness and storage availability.

Social storage systems [1], [2], [3] are becoming increasingly popular compared to the existing data backup systems like local, centralized and P2P systems. An endogenously built symmetric social storage model and its aspects like the utility of each agent, bilateral stability, contentment, and efficiency have been extensively discussed in [4]. We include heterogeneity in this model by using the concept of Social Range Matrix from [5]. Now, each agent is concerned about its perceived utility, which is a linear combination of its utility as well as others utilities (depending upon whether the pair are friends, enemies or do not care about each other). We derive conditions when two agents may want to add or delete a link, and provide an algorithm that checks if a bilaterally stable network is possible or not. Finally, we take some special Social Range Matrices and prove that under certain conditions on network parameters, a bilaterally stable network is unique.

This paper investigates the impact of link formation between a pair of agents on resource availability of other agents in a social cloud network, which is a special case of socially-based resource sharing systems. Specifically, we study the correlation between externalities, network size, and network density. We first conjecture and experimentally support that if an agent experiences positive externalities, then its closeness (harmonic centrality measure) should increase. Next, we show the following for ring networks: in less populated networks no agent experiences positive externalities; in more populated networks a set of agents experience positive externalities, and larger the distance between agents forming a link, more the number of beneficiaries; and the number of beneficiaries is always less than the number of non-beneficiaries. Finally, we show that network density is inversely proportional to positive externalities, and further, it plays a crucial role in determining the kind of externalities.

We model social storage systems as a strategic network formation game. We define the utility of each player in the network under two different frameworks, one where the cost to add and maintain links is considered in the utility function and the other where budget constraints are considered. In the context of social storage and social cloud computing, these utility functions are the first of its kind, and we use them to define and analyze the social storage network game. We, then, present the pairwise stability concept adapted for social storage where both addition and deletion of links require mutual consent, as compared to mutual consent just for link addition in the pairwise stability concept defined by Jackson and Wolinsky [35]. Mutual consent for link deletion is especially important in the social storage setting. For symmetric storage networks, we prove that there exists a unique neighborhood size, independent of the number of players, where no pair of users has any incentive to increase or decrease their neighborhood size. We call this neighborhood size as the stability point. We provide some necessary and sufficient conditions for pairwise stability of social storage networks. Further, given the number of players and other parameters, we discuss which pairwise stable networks would evolve. We also show that in a connected pairwise stable network there can be at most one player with neighborhood size one less than (or one more than) the stability point.

In recent years, various kinds of distributed resource sharing setups have been proposed by taking social relationships into consideration. These dissimilar resource sharing setups are tagged as Social Cloud. These setups have appeared in various distributed computing forms such as community cloud, grid, volunteer computing and network services. Such setups are discrete in nature, and hence, do not conceptualize the totality of the Social Cloud concept. In fact, it is difficult to conceptualize Social Cloud without a general framework. There are three main objectives of this work. First, to present a general framework of Social Cloud. Second, to report various Social Cloud setups with corresponding architectural prototypes and current trends. Third, to discuss research challenges.

Social Clouds have been gaining importance because of their potential for efficient and stable resource sharing without any (monetary) cost implications . There is a need, however, to look at how a social structure or relationship evolves to build a Social Cloud (by identifying factors that affect the social structure) and how social structure impacts individual resource sharing behavior. This paper presents a pairwise resource (or pairwise service) sharing social network model to explore the interdependence between social structure and resource (service) availability for an individual user or player. The paper also investigates effects of social structure on individual resource availability. Further, the paper analyzes positive and negative externalities, and aims to characterize stable social clouds.

The idea of composite cloud service has been emerging to reduce negative impact of cloud bursting. The novel idea of composite cloud services is achieved by forming a dynamic cloud collaboration platform among cloud providers. An important prerequisite of dynamic collaborative cloud formation is to reduce the cost of infrastructure and prevent loss to business enterprises owing to cloud bursting. The major concern in dynamic cloud collaboration is to minimize conflict among cloud providers and ensure each provider's benefit. In recent years several market based models have been proposed that deal with twofold objectives. First, conflict minimization among providers and Second, benefit maximization of the providers. However, existing combinatorial auction based market models that attempt to achieve dynamic cloud collaboration are computationally in efficient. In this paper we have proposed cloud partner matching algorithm to facilitate partner selection process. Our proposed cloud partner matching algorithm minimizes conflicts among cloud providers by mutual consent.

Wikipedia is the world's largest collaboratively edited source of encyclopedic information repository consisting almost 1.5 million articles and more than 90,000 contributors. Although, since its inception on 2001, the numbers of contributors were huge, A study made in 2009 found that members (contributors) may initially contribute to site for pleasure or being motivated by an internal drive to share his knowledge. But latter they are not motivated to edit the related articles so that quality of the articles could be improved [1] [5]. In our paper we address above problem in economics perspective. Here we propose a novel scheme to motivate the contributors of Wikipedia with the mechanism design theory that is the most emerging tool at present to address the situation when data is privately held with the agents.

In multiprogramming environment, where two processes may compete for a finite number of instances of the same resource type, occurrence of deadlock between them is very usual situation. Key task is to get the appropriate recovery from deadlock such that every process get fair result and resources must not preempted from same process every time. This paper proposes a payoff matrix approach that resolve these bottleneck. Proposed algorithm can efficiently find an algorithm for deadlock recovery. In this paper two player zero sum game is played using mixed strategy mechanism, a probabilistic approach where two process are acting as players and environment is fair. The time complexity of proposed algorithm for recovering two process deadlock which hold the instances of same resource type is constant to recover from the deadlock.