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.
Cloud Computing Environment (CCE) is a newly rudimentary knowledge in the IT industry. Central to these problems lies in the establishment of an active LB algorithm. The network load can be CPU load, memory limit, postponement, or system load. In the proposed algorithm, Load Balancing (LB) done by considering priority policy. An Efficient and Dynamic Load Balancing Approach in Cloud Computing (EDBA-CC) proposed, and the related algorithm executed on CloudSim (CS). A resource allocation approach that takes into account Resource Utilization (RU) would lead to better energy efficiency. The outcomes indicate the effectiveness of the proposed algorithm. The outcomes exhibited that the EDBA-CC algorithm reduced Response Time (RT). The decreasing in RT is about 2.23 ms when the instruction length was 275 Byte, and the decreasing became more obviously with 10.12 ms for RT and 5.54 ms for RT when the instruction length was 2000 Byte.
Maintaining the quality of service (QoS) related parameters is an important issue in cloud management systems. The lack of such QoS parameters discourages cloud users from using the services of cloud service providers. The proposed task scheduling algorithms consider QoS parameters such as the latency, make-span, and load balancing to satisfy the user requirements. These parameters cannot sufficiently guarantee the desired user experience or that a task will be completed within a predetermined time. Therefore, this study considered the cost-enabled QoS-aware task (job) scheduling algorithm to enhance user satisfaction and maximize the profit of commercial cloud providers. The proposed scheduling algorithm estimates the cost-enabled QoS metrics of the virtual resources available from the unified resource layer in real-time. Moreover, the virtual machine (VM) manager frequently updates the current state-of-the art information about resources in the proposed scheduler to make appropriate decisions. Hence, the proposed approach guarantees profit for cloud providers in addition to providing QoS parameters such as make-span, cloud utilization, and cloud utility, as demonstrated through a comparison with existing time-and cost-based task scheduling algorithms.
Underwater Wireless Sensor Networks is effective and intelligent utilization of energy for routing protocol in longer network lifetime. Energy Consumption and load balancing are the vital roles for a network lifetime. The use of load balancing in WSN is granted as the best resource of sink mobility which protects energy sources to organize. The aim of this paper is to evaluate various deployed strategies involving sink mobility. Multiple mobile sinks are capable of performing computational operations like collecting information from electric joints instantly, storage and also communication capability. It evaluates the results and the effect of sink mobility by comparing with another routing protocol GEDAR.
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