Weight Queue Dynamic Active Queue Management Algorithm

The current problem of packets generation and transformation around the world is router congestion, which then leads to a decline in the network performance in term of queuing delay (D) and packet loss (PL). The existing active queue management (AQM) algorithms do not optimize the network performance because these algorithms use static techniques for detecting and reacting to congestion at the router buffer. In this paper, a weight queue active queue management (WQDAQM) based on dynamic monitoring and reacting is proposed. Queue weight and the thresholds are dynamically adjusted based on the traffic load. WQDAQM controls the queue within the router buffer by stabilizing the queue weight between two thresholds dynamically. The WQDAQM algorithm is simulated and compared with the existing active queue management algorithms. The results reveal that the proposed method demonstrates better performance in terms mean queue length, D, PL, and dropping probability, compared to gentle random early detection (GRED), dynamic GRED, and stabilized dynamic GRED in both heavy or no-congestion cases. In detail, in a heavy congestion status, the proposed algorithm overperformed dynamic GRED (DGRED) by 13.3%, GRED by 19.2%, stabilized dynamic GRED (SDGRED) by 6.7% in term of mean queue length (mql). In terms of D in a heavy congestion status, the proposed algorithm overperformed DGRED by 13.3%, GRED by 19.3%, SDGRED by 6.3%. As for PL, the proposed algorithm overperformed DGRED by 15.5%, SDGRED by 19.8%, GRED by 86.3% in term of PL.

The disasters queue with working breakdowns and impatient customers

We consider the M/M/1 queue with disasters and impatient customers. Disasters only occur when the main server being busy, it not only removes out all present customers from the system, but also breaks the main server down. When the main server is down, it is sent for repair. The substitute server serves the customers at a slow rate(working breakdown service) until the main server is repaired. The customers become impatient due to the working breakdown. The system size distribution is derived. We also obtain the mean queue length of the model and mean sojourn time of a tagged customer. Finally, some performance measures and numerical examples are presented.

Exploring Analytical Models for Performability Evaluation of Virtualized Servers using Dynamic Resource

Virtualization of resources is a widely accepted technique to optimize resources in recent technologies. Virtualization allows users to execute their services on the same physical machine, keeping these services isolated from each other. This paper proposes the analytical models for performability evaluation of virtualized servers with dynamic resource utilization. The performance and avalability models are considered separately due to the behaviour of the proposed system. The well-known Markov Reward Model (MRM) is used for the solution of the analytical model considered together with an exact spectral expansion and product form solution. The dynamic resource utilization is employed to enhance the QoS of the proposed model which is another major issue in the performance characterization of virtulazilation. In this paper, the performability output parameters, such as mean queue length, mean response time and blocking probability are computed and presented for the proposed model. In addition, the performability results obtained from the analytical models are validated by the simulation (DES) results to show the accuracy and effectiveness of the proposed work. The results indicate the proposed modelling results show good agreement with DES and understand the factors are very important to improve the QoS.

Performance evaluation of proposed load balancing algorithm with unstable concurrent programs

<span>IoT is the succeeding cohort of the digital computing environment. A swift progression in the IoT deployment and its applications are on the rise. Improving load balancing mechanisms induces healthier performance of the internet based computing as higher number of users can be comfortable. Implementing full services for tasks with unstable concurrency is an uphill process. One of the encounters allied with this administration is the task partition among the applications, regularly referred as concurrent programs. Through load balancing not only resources are equally utilized but also concurrent job’s response time can be promoted. Therefore, in this paper the widely used load balancing algorithms are investigated and yet the proposed algorithm is introduced. Simulation is employed in order to compare the performance metrics such as mean queue length, utilization and throughput between the recommended and existing algorithms. The proposed algorithm confirms the load balancing and outperforms when processing unstable concurrent programs.</span>

IGRED: An Improved Gentle Random Early Detection Method for Management of Congested Networks

Controlling congested router buffers of a network has a crucial role in improving network’s performance. This paper proposes a novel Active Queue Management (AQM) method named Improved Gentle Random Early Detection (IGRED) that based on GRED algorithm, which counted as one of the popular AQM methods. The proposed is mainly developed to overcome the problems faced with classic GRED. The initial packet-dropping probability depends on several parameters such as the average queue length, maximum value of packet dropping probability, minimum and maximum thresholds, etc. IGRED reduces its reliance on the GRED’s parameters through shrinking these parameters. The results shows, when congestion is taken place, the proposed IGRED provides more satisfactory performance with reference to mean queue length, average queuing delay, and overflow packet loss probability.

An M/M/1 Queue with Working Vacation and Vacation Interruption Under Bernoulli Schedule

This work deals with M/M/1 queue with Vacation and Vacation Interruption Under Bernoulli schedule. When there are no customers in the system, the server takes a classical vacation with probability p or a working vacation with probability 1-p, where . At the instants of service completion during the working vacation, either the server is supposed to interrupt the vacation and returns back to the non-vacation period with probability 1-q or the sever will carry on with the vacation with probability q. When the system is non empty after the end of vacation period, a new non vacation period begins. A matrix geometric approach is employed to obtain the stationary distribution for the mean queue length and the mean waiting time and their stochastic decomposition structures. Numerous graphical demonstrations are presented to show the effects of the system parameters on the performance measures.

Social optimization in M/M/1 queue with working vacation and N-policy

This paper deals with the N-policy M/M/1 queueing system with working vacations. Once the system becomes empty, the server begins a working vacation and works at a lower service rate. The server resumes regular service when there are N or more customers in the system. By solving the balance equations, the stationary probability distribution and the mean queue length under observable and unobservable cases are obtained. Based on the reward-cost structure and the theory of Markov process, the social welfare function is constructed. Finally, the impact of several parameters and information levels on the mean queue length and social welfare is illustrated via numerical examples, comparison work shows that queues with working vacations(WV) and N-policy have advantage in controlling the queue length and improving the social welfare.

Transient solution of /G/1 with Second Optional Service Subject to Reneging during Vacation and Breakdown time

In this paper, we present a batch arrival non- Markovian queuing model with second optional service. Batches arrive in Poisson stream with mean arrival rate ?, such that all customers demand the first essential service, whereas only some of them demand the second "optional" service. We consider reneging to occur when the server is unavailable during the system breakdown or vacations periods. The time-dependent probability generating functions have been obtained in terms of their Laplace transforms and the corresponding steady state results have been derived explicitly. Also the mean queue length and the mean waiting time have been found explicitly.