Cloud Service Negotiation Research Articles

Game the Oretic Approach for Cloud Service Negotiation

Cloud computing is a booming technology in the area of digital markets. Tackling the nonfunctional characteristics is a big challenge between service consumers (SC) and service providers (SP). Without proper negotiation between the participants specifying their quality of service (QoS) requirements, service level agreement (SLA) cannot be achieved. Two strategies that are commonly prevalent in the negotiation process are concession model and trade off model. The concession model assures the service consumer (SC) receiving the services on time without any deferment. But service consumer has only limited utility. To balance the utility and achievement rates, the authors propose a mixed negotiation approach for cloud service negotiation, which is based on “Game of Chicken.” Extensive results show that a mixed negotiation approach brings equal amount of satisfaction to both service consumer and service provider in terms of achieving higher utility and outperforms the concession approach, while taking fewer time delays than that of a tradeoff approach.

An Overview of Current Multi-Attribute Techniques in Double Auction Frameworks

Double auction is becoming the preferred negotiation protocol for cloud service negotiation due to its economic efficiency, capability in facilitating dynamic pricing, and suitability for handling a large number of customers and service providers. However, as far as this research work is concerned, there is no framework using double auction that simultaneously and comprehensively addresses the heterogeneity of cloud services in multi-attributes negotiation. Before such a framework can be designed, suitable multi-attributes negotiation techniques and its attributes should be identified. Therefore, this paper’s objective is to distinguish and provide an overview of multi-attributes techniques used in double auction negotiations. The sources are from the Scopus Database. It is found that the current multi-attributes techniques lacked in addressing the preferential dependency, selective attributes and utility optimization simultaneously in double auction frameworks. These concerns need to be addressed in order to devise a practical framework. The future direction for double auction framework in multi-attributes negotiation is suggested.

Cloud service negotiation framework for real-time E-commerce application using game theory decision system

A major demanding issue is developing a Service Level Agreement (SLA) based negotiation framework in the cloud. To provide personalized service access to consumers, a novel Automated Dynamic SLA Negotiation Framework (ADSLANF) is proposed using a dynamic SLA concept to negotiate on service terms and conditions. The existing frameworks exploit a direct negotiation mechanism where the provider and consumer can directly talk to each other, which may not be applicable in the future due to increasing demand on broker-based models. The proposed ADSLANF will take very less total negotiation time due to complicated negotiation mechanisms using a third-party broker agent. Also, a novel game theory decision system will suggest an optimal solution to the negotiating agent at the time of generating a proposal or counter proposal. This optimal suggestion will make the negotiating party aware of the optimal acceptance range of the proposal and avoid the negotiation break off by quickly reaching an agreement.

Agent-based cloud service negotiation architecture using similarity grouping approach

Challenges and issues in the field of cloud service negotiation framework optimization have been an active area of research. During service level agreement, the probability of negotiation conflict between the service consumers and providers is high. This may arise due to aggressive behavior, selfish misperception, vague preferences and uncertain goals of the negotiating participants. One of the key challenges identified in negotiation framework is optimizing the negotiation conflict among the negotiators. In order to minimize such conflicts, existing frameworks group the negotiation pairs that contain similar and non-aggressive behavioral patterns by exploiting the distance, binary, context dependent and fuzzy similarity approaches. These approaches get better success rate only if the dimensionality of negotiator attributes is low. As emerging real-time cloud service negotiation applications are characterized by negotiation attributes of high dimensionality, the existing approaches are inappropriate for these applications. In addition, the existing approaches group the negotiation pairs using distances based measure in two-dimensional negotiation attribute, whose value will vary for high-dimensional attributes. In this work, an Angle-based Similarity Grouping (ASG) approach is proposed that appropriately groups the highly cooperative negotiation pairs and thereby increases the success rate and decreases communication overhead.

Adaptive neuro-fuzzy behavioral learning strategy for effective decision making in the fuzzy-based cloud service negotiation framework

Adaptive neuro-fuzzy behavioral learning strategy for effective decision making in the fuzzy-based cloud service negotiation framework

Business Level Objectives of Customer for Autonomous Cloud Service Negotiation

Business Level Objectives of Customer for Autonomous Cloud Service Negotiation

Multi-user utility pattern based cloud service negotiation for quality of service improvement: an implicit interest prediction approach

Multi-user utility pattern based cloud service negotiation for quality of service improvement: an implicit interest prediction approach

Multi-user utility pattern based cloud service negotiation for quality of service improvement: an implicit interest prediction approach

The growing deployment of cloud services increases the responsibility of cloud service provider in meeting consumer satisfaction in great measure. As the interest of the user changes in time and the number of service providers are growing the cloud user has more options in choosing the required service. But the problem of service negotiation must be handled by all the service providers in order to improve the quality of service. To solve the issue of service negotiation, a multi-user utility pattern based service negotiation approach is discussed in this paper. The method monitors the service negotiation values and keeps track of services accessed by different cloud user. It also maintains a trace of sequence of service access based on user's interest. The proposed technique uses the implicit tracking approach to predict the interest of the user by monitoring the service access without the knowledge of the end user and generate a pattern called utility pattern. Based on the generated pattern, the most impacting services are ranked according to the implicit activities of different users. The ranked services are given to the user to select a single service to fulfil the request. The proposed technique improves the performance of cloud environment to 95% and increases the satisfaction of the cloud user.

Dynamic Pricing for Cloud Service Negotiation

Big players in cloud service market like Microsoft, Amazon and Google keeps changing their service price. Increasing cloud service offerings have motivated cloud providers to develop cloud service marketplace such as AWS, Google Apps and Cloud Surfing. However, these marketplaces lack dynamic pricing mechanism. The idea of dynamic pricing in the cloud services market has emerged in recent years and there is a need to design and implement an appropriate pricing model for managing the service demand and capacity. This paper reviews dynamic pricing implementation in cloud services and similar areas. This paper reviews recent concurrent cloud SLA negotiation frameworks. A concurrent cloud SLA negotiation mechanism with adaptive pricing is proposed. The proposed mechanism is designed to address multiplicity, information sharing and complexity issues in current frameworks. © 2016 American Scientific Publishers. All rights reserved.

Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model.

Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.

Cloud Service Negotiation in Internet of Things Environment: A Mixed Approach

Internet of Things (IoT) allows connected objects to communicate via the Internet. IoT can benefit from the unlimited capabilities and resources of cloud computing. Also, when coupled with IoT, cloud computing can in turn deal with real world things in a more distributed and dynamic manner. As the cloud market becomes more open and competitive, Quality of Service (QoS) will be more important. However, cloud providers and cloud consumers have different, and sometimes opposite, preferences. If such a conflict occurs, a Service Level Agreement (SLA) cannot be reached without negotiation. A tradeoff negotiation approach can outperform a concession approach in terms of utility, but may incur more failures if information is incomplete. To balance utility and success rate, we propose a mixed approach for cloud service negotiation, which is based on the “game of chicken.” In particular, if one is uncertain about the strategy of its counterpart, it is best to mix concession and tradeoff strategies in negotiation. To evaluate the effectiveness of this approach, we conduct extensive simulations. Results show that a mixed negotiation approach can achieve a higher utility than a concession approach, while incurring fewer failures than a tradeoff approach.

Cloud service negotiation: a research report

As the cloud market becomes more open and competitive, Quality of Service (QoS) will be more important. To allow cloud consumers to express their QoS requirements, and negotiate them with cloud providers, we argue for cloud service negotiation. This paper outlines a research roadmap, reviews the state of the art and reports our work on cloud service negotiation. Three research problems that we formulate are QoS measurement, QoS negotiation and QoS assurance. To address QoS measurement, we initiate a quality model for cloud services, called CLOUDQUAL, which specifies six quality dimensions and five quality metrics. To address QoS negotiation, we present a mixed negotiation approach for cloud services, which is based on the ‘game of chicken’ and can balance utility and success rate. To address QoS assurance, we propose a QoS-driven resource allocation method for cloud services, which can meet users’ QoS requirements while minimising resources consumed.

Agent-Based Cloud Computing

Agent-based cloud computing is concerned with the design and development of software agents for bolstering cloud service discovery, service negotiation, and service composition. The significance of this work is introducing an agent-based paradigm for constructing software tools and testbeds for cloud resource management. The novel contributions of this work include: 1) developing Cloudle: an agent-based search engine for cloud service discovery, 2) showing that agent-based negotiation mechanisms can be effectively adopted for bolstering cloud service negotiation and cloud commerce, and 3) showing that agent-based cooperative problem-solving techniques can be effectively adopted for automating cloud service composition. Cloudle consists of 1) a service discovery agent that consults a cloud ontology for determining the similarities between providers' service specifications and consumers' service requirements, and 2) multiple cloud crawlers for building its database of services. Cloudle supports three types of reasoning: similarity reasoning, compatibility reasoning, and numerical reasoning. To support cloud commerce, this work devised a complex cloud negotiation mechanism that supports parallel negotiation activities in interrelated markets: a cloud service market between consumer agents and broker agents, and multiple cloud resource markets between broker agents and provider agents. Empirical results show that using the complex cloud negotiation mechanism, agents achieved high utilities and high success rates in negotiating for cloud resources. To automate cloud service composition, agents in this work adopt a focused selection contract net protocol (FSCNP) for dynamically selecting cloud services and use service capability tables (SCTs) to record the list of cloud agents and their services. Empirical results show that using FSCNP and SCTs, agents can successfully compose cloud services by autonomously selecting services.