- Open Access
Dynamic social cloud management scheme based on transformable Stackelberg game
© Kim. 2016
- Received: 22 October 2015
- Accepted: 1 February 2016
- Published: 13 February 2016
With the ubiquitous nature of social networks and cloud computing, we are starting to explore a new way to interact with and exploit these developing paradigms. Social cloud (SC) is a service or resource sharing framework on top of social networks and built on the trust-based social relationships. In recent years, the idea of SC has been gaining importance because of its potential applicability. This article introduces a novel SC management scheme with a view of game theory model and reciprocal resource sharing mechanism. In particular, we devise a new transformable Stackelberg game to coordinate the interdependence between social structure and resource availability for individual users. Our proposed scheme constantly monitors the current SC system conditions and adaptively exploits the available resources while ensuring mutual fairness. The simulation results show that the proposed method is effective in distributed SC environments and adaptively supports application executions timely and ubiquitously.
- Social cloud system
- Transformable Stackelberg game
- Dynamic resource sharing
- Reciprocal fairness
- Game theory
Digital relationships between individual people become more and more embedded in our daily actions, and they can be powerful influences in our real-life. Moreover, we are now connected with all our social networks through mobile devices. The increasing ubiquity of social networks is evidenced by the growing popularity of social network services. A social network service consists of a representation of each user, his or her social links, and a variety of additional services. Usually, social networks provide a platform to facilitate communications and resource sharing between users while modeling real-world relationships. Therefore, a variety of social network services have extended beyond simple communication among users [1–3].
With the advent of social networks, cloud computing is becoming an emerging paradigm to provide a flexible stack of computing, software, and storage services. In a scalable and virtualized manner over networks, cloud users can access to fully virtualized hardware resources. The adoption of cloud computing technology is attractive; users obtain cloud resources, whose management is partly automated and can be scaled almost instantaneously. However, with the rapid development of cloud computing, critical issues of cloud computing technology have emerged. In general, modern cloud applications are characterized by assuming a constant environment. But real-world environments are open, dynamic, and unpredictable [4–7].
In social networks, individual users are bound by finite resource capacity and limited capabilities. However, some users may have surplus resource capacity or capabilities. Therefore, the superfluous resource could be shared for a mutual benefit. Within the context of a social network, users may wish to share resources without payment and utilize a reciprocal credit based on the trust model [8, 9]. To satisfy this goal, a new concept, social cloud (SC) was introduced by combining the methodologies of social networks and cloud computing. SC is a novel scalable computing model where resources are beneficially shared among a group of social network users. From , we rehearse the formal definition of SC as follows: A social cloud is a resource and service sharing framework utilizing relationships established between members of a social network. Based on the cloud computing technique, SC model is used to enable virtualized resource sharing through service-based interfaces .
To construct the SC system in a real-world environment, there are many challenges that need to be carefully considered. First of all, the concept of SC focuses on the sharing rather than sale of resources. Using sharing preferences, the social context of exchange is accentuated along with the social ties of individual users . However, social relationships are not simply edges in a graph. There are many different types of relationship; different users will associate different levels of trust to different relationship contexts and have different reliability, trustworthiness, and availability. Therefore, users may have very specific preferences with whom they interact. To design an effective SC control scheme, it is necessary to take into account the preferences and perceptions of users toward one another .
Under widely dynamic SC system conditions, end users can be assumed as intelligent rational decision-makers, and they select a best-response strategy to maximize their expected payoffs. This situation is well-suited for the game theory. Game theory is a field of applied mathematics that provides an effective tool to model interactions among independent decision-makers. It can describe the reactions of one set of decision-makers to another and analyze the situations in terms of conflict and cooperation. Therefore, game theory is really useful in analyzing the mutual interactions among multi-users. Thus, it can be a major paradigm to retain an equilibrium between different users that feature complex interactive relations .
In 1934, German economist H. V. Stackelberg proposed a hierarchical strategic game model based on two kinds of different decision-makers. Under a hierarchical decision-making structure, one or more players declare and announce their strategies before the other players choose their strategies. In game theory terms, the declaring players are called as leaders while the players who react to the leaders are called as followers. Originally, the Stackelberg game model was developed to explain the monopoly of industry. The leader is the incumbent monopoly of the industry, and the follower is a new entrant; it can be the static bilevel optimization model . In this study, we have further extended the classical Stackelberg model and developed a novel game mode, called transformable Stackelberg (TS) game model. In the TS game, each player can be a leader or a follower as the case may be. Therefore, the position of game players is dynamically transformable according to current conditions.
Motivated by the above discussion, we propose a new SC resource sharing scheme based on the TS game model. TS game model is a useful framework for designing decentralized mechanisms, such that users in SC systems can self-organize into the mutually satisfactory resource sharing process. This self-organizing feature can add autonomics into SC systems and help to ease the heavy burden of complex centralized control algorithms. Especially, we pay serious attention to trust evaluation, repeated interactions, and iterative self-learning techniques to effectively implement our resource sharing process. In the proposed scheme, such techniques have been incorporated into the TS game model and work together toward an effective system performance. Therefore, we can induce all users to share their resources adaptively. The major contributions of the proposed scheme are (i) the adjustable dynamics considering the current SC environments, (ii) the interactive learning process based on the iterative feedback mechanism, (iii) the sophisticated combination of the reciprocal relationship and incentive mechanism, and (iv) practical approach to effectively reach a desirable solution. Other existing schemes [8, 10, 12–16] cannot offer these attractive features.
1.1 Related work
The area of numerical methods or algorithms for efficient SC control problems has been extensively studied and has received considerable attention in recent years [8, 10, 12–16]. In , Lee et al. presented the design and development of the architecture of the just-in-time social cloud and experimental methods to measure the just-in-time social influences. Just-in-time social cloud service can better guide people toward their long-term goals by influencing their choices at the moment and potentially mitigating behavioral biases. They attempted to design a social platform that can be programmed to benefit human being’s long-term goals by mitigating the inter-temporal biases people have toward present . The scheme in  was developed for leveraging the online relationships to form a dynamic social cloud, while enabling users to share heterogeneous resources within the context of a social network. The socially corrective mechanism was used to enable a cloud-based framework for long term sharing with lower privacy concerns and security overheads that were present in traditional cloud environments .
Ali et al. developed the Cloud Resource Bartering (CRB) model for sharing user’s computational resources through a social network . The CRB model allowed users of online social network to share their cloud resources without money changing hands. This scheme linked a social network with the computational cloud to create a social cloud so that users can share their part of the cloud with their social community . The scheme in  considered the effect of reputation when parties interacted in social cloud to find a new way realizing mutual cooperation. Parities in the social cloud were rational who valued their reputation. Cooperation can boost their reputation, so they had incentives to cooperate with others such that they may get a higher utility. The basic idea in  was to add reputation deriving from social cloud as part of the utility.
The Social Compute Cloud (SCC) scheme  was developed for the SC interaction system. This scheme has presented a social compute cloud platform that enabled the sharing of infrastructure resources between friends via digitally encoded social relationships. To construct a social compute cloud, the SCC scheme accessed users’ social networks, allowed users to elicit sharing preferences, and utilized matching algorithms to enable preference-based socially aware resource allocation. The Incentive-based Social Cloud (ISC) scheme  was designed to model the selfish behavior of the users who were supplying resources and aiming to maximize their own benefits. Based on the reputation-based pricing and collective punishment mechanism, the ISC scheme compelled suppliers to change their selfish strategies in a manner that improved the efficiency of the SC system.
The Reputation-based Social Cloud (RSC) scheme  added the concept of reputations as part of the utility. This scheme described the architecture and interaction between two rational parties in the social cloud, where two parties received their opponent’s trust or reputation from the social cloud. In the RSC scheme, the reputation was affected by the interactions with other parties in the social network. As mentioned above, numerous studies have shown how social networks create social influences on people’s choices across time and space. In this study, we compared the performance of the proposed scheme with the existing schemes in [10, 12] and  to confirm the superiority of our approach.
This paper is organized as follows. Section 2 describes how insights from TS game model would help us to incorporate learning mechanism into the SC control scheme and to guide selfish users to achieve a globally desirable SC system performance. Afterwards, the main step of the proposed SC control algorithm is presented. In Section 3, performance evaluation results are presented along with comparisons with the schemes proposed in [10, 12] and . Through simulation, we show the ability of proposed scheme to achieve high accuracy and promptness in dynamic SC environments. Finally, we end up with some concluding remarks in Section 4.
The simulated system consisted of 30 social network users for the SC platform.
We followed the traditional network topology, decentralized, and partially connected topology.
In the network coverage area, network mobile devices executed elastic applications. For each device, application service request was Poisson with rate ρ (services/s) and the range of the offered service load was varied from 0 to 3.0.
Each mobile device has a different resource amount. There were five resource capacities for the devices and the device i’s capacity (ℭ i,i ∈ ℕ) was ℭ i ∈ (10, 12.5, 15, 17.5, and 20 Mbps).
To reduce the computation complexity, the amount of resource allocation is specified in terms of basic units (BUs), where one BU is the minimum amount (e.g., 320 kbps in our system) for the resource sharing process.
The service durations of applications are exponentially distributed with different means for different multimedia application types.
Network performance measures obtained based on 100 simulation runs were plotted as a function of the offered service load.
The performance criteria obtained through simulation were resource usability, CCE convergence ratio, and normalized system throughput.
Table 1 shows the system parameters used in the simulation. In order to emulate a real SC system and perform a fair comparison, we used the system parameters for a realistic simulation model.
In this paper, we compared the performance of the proposed scheme with existing schemes: the SCC scheme , ISC scheme , and RSC scheme . These existing schemes were recently developed as effective SC management algorithms; all the schemes have polynomial time complexity. Compared to these schemes, we can confirm the superiority of our proposed approach.
As expected, CCE convergence ratio decreases while increasing service loads or decreasing Γ Λ values.
The simulation results presented in Figs. 1 and 2 demonstrate the performance of the proposed and other existing schemes and verify that the proposed scheme can provide attractive network performance. The proposed scheme constantly monitors the current conditions for an adaptive SC system management and successfully exhibits excellent performance. As expected, the performance enhancements provided by the proposed scheme outperformed the existing schemes [10, 12, 13]. The curves shown in Fig. 3 demonstrate the CCE convergence ratio of our proposed scheme. This result is intuitively correct.
The ever increasing use of social networks and arrival of new computing paradigms like cloud computing has urged the need to integrate these platforms for the better and inexpensive usage of resources. Sharing cloud resources in such environments would be very helpful. This article addresses a new resource control algorithm for SC systems. Using the TS game model, users iteratively observed the received payoffs and repeatedly modified their altruistic propensities to effectively manage SC resources. The proposed scheme enables the sharing of SC resources between users via reciprocal cooperative relationships and can effectively approach the CCE status using a step-by-step feedback process. Compared with the existing schemes, the simulation results confirmed that the proposed game-based method could improve the performance under dynamically changing SC system environments whereas other existing schemes could not offer such an attractive performance. For future research, the SC paradigm presents a rich environment. One major area of future work is adapting the SC protocols that facilitate big data streaming from SC to Internet of Things (IoT). In addition, we are also looking further at QoS and QoE, as well as data security, privacy, and reliability issues. In parallel to these efforts, we plan to deploy the social storage cloud to provide a platform for further experimentation. In particular, we aim to explore system performance and user interactions on a much larger scale.
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP (Institute for Information & communications Technology Promotion) and was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01060835).
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