Unreliable Server Research Articles

Analysis of M/M/1 queueing model with removable and unreliable server, partial breakdown during working vacation, setup with repair

Analysis of M/M/1 queueing model with removable and unreliable server, partial breakdown during working vacation, setup with repair

Grey wolf algorithm for cost optimization of cloud computing repairable system with [formula omitted]-policy, discouragement and two-level Bernoulli feedback

With the increasing reliance on cloud computing as the foundational infrastructure for technological operations, the urgency and efficacy with which failed virtual machines can be successfully repaired earns significant weight. In this study, we have presented a queueing model that analyzes the repair process of failed virtual machines in cloud computing system. This model includes various important components, such as control N-policy, server unreliability, discouragement behavior of failed virtual machines (like balking and reneging), retention of reneged machines, redundancy, and two-level Bernoulli feedback. A steady-state performance analysis has been performed. The proposed model provides practical suggestions for cloud service providers to improve the reliability and availability of their services, which insights more than theoretical frameworks. This study is unique in the field of queueing models of cloud computing machining environment, as it incorporates parallel consideration of control N policies, balking, reneging, retention, server vacation, two-level Bernoulli feedback and unreliable server behavior. A thorough examination of the behavior of key performance indicators has been conducted and presented using detailed graphical representations. In addition, a cost function is formulated for the proposed model. Further, the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) techniques are utilized to optimize the total cost function, thereby gaining valuable insights into the system’s behavior across various conditions as well as to compare the outcomes of GWO and PSO.

Graph Crypto‐Stego System for Securing Graph Data Using Association Schemes

Cryptography has recently become a critical area to research and advance in order to transmit information safely and securely among various entities, especially when the transmitted data is classified as crucial or important. This is due to the increase in the use of the Internet and other novel communication technology. Many businesses now outsource sensitive data to a third party because of the rise of cloud computing and storage. Currently, the key problem is to encrypt the data such that it may be stored on an unreliable server without sacrificing the ability to use it effectively. In this paper, we propose a graph encryption scheme by using cryptography and steganography. Data is encrypted using association schemes over finite abelian groups and then hiding the encrypted data behind randomly chosen cover image. We implemented and evaluated the efficiency of our constructions experimentally. We provide experimental results, statistical analysis, error analysis, and key analysis that demonstrates the appropriateness and efficiency of the proposed technique.

Performance analysis and cost investigations for state-dependent single unreliable server finite queue under F-policy using GA and QNM

State-dependent queues are essential as they accurately capture the dynamic behavior of systems, enabling more realistic modeling and analysis of various real-world scenarios. The present investigation deals with a state-dependent single unreliable server finite queueing model under admission control F-policy. The admission control F-policy is a valuable tool to control the congestion problem of customers where the queue forms. In the proposed model, the server is prone to breakdown and can fail at any time. There is a two-phase repair facility available to address server failures. Chapman–Kolmogorov (C–K) steady-state equations based on the birth–death process are formed and solved using the matrix analytic method to formulate a mathematical model. By setting suitable values for state-dependent parameters, some particular models, such as the machine repair problem (MRP) and queueing model with customers’ balking and feedback, can also be deduced. Furthermore, various queueing indices are established to predict the validity of state-dependent queues. A total cost function for the system is constructed to enhance customer service while minimizing costs. This cost function is then optimized using a genetic algorithm (GA) and quasi-Newton method (QNM). The cost optimization in the state-dependent queueing model enables businesses to optimize resource allocation and achieve cost-efficient service delivery, leading to improved profitability and customer satisfaction.

Robustness of the cμ-Rule for an Unreliable Single-Server Two-Class Queueing System with Constant Retrial Rates

We study the robustness of the cμ-rule for the optimal allocation of a resource consisting of one unreliable server to parallel queues with two different classes of customers. The customers in queues can be served with respect to a FIFO retrial discipline, when the customers at the heads of queues repeatedly try to occupy the server at a random time. It is proved that for scheduling problems in the system without arrivals, the cμ-rule minimizes the total average cost. For the system with arrivals, it is difficult directly to prove the optimality of the same policy with explicit relations. We derived for an infinite-buffer model a static control policy that also prescribes the service for certain values of system parameters exclusively for the class-i customers if both of the queues are not empty, with the aim to minimize the average cost per unit of time. It is also shown that in a finite buffer case, the cμ-rule fails.

Performance Analysis of a Retrial Queueing System with Optional Service, Unreliable Server, Balking and Feedback

This paper considers a Markovian retrial queueing system with an optional service, unreliable server, balking and feedback. An arriving customer can avail of immediate service if the server is free. If the potential customer encounters a busy server, it may either join the orbit or balk the system. The customers may retry their request for service from the orbit after a random amount of time. Each customer gets the First Essential Service (FES). After the completion of FES, the customers may seek the Second Optional Service (SOS) or leave the system. In the event of unforeseen circumstances, the server may encounter a breakdown, at which point an immediate repair process will be initiated. After the service completion, the customer may leave the system or re-join the orbit if not satisfied and demand regular service as feedback. In this investigation, the stationary queue size distributions are framed using a recursive approach. Various system performance measures are derived. The effects induced by the system parameters on the performance metrics are numerically and graphically analysed.

Performance analysis of a multi server retrial queueing system with unreliable server, discouragement and vacation model

In this paper, we investigate a Markovian multi server retrial queueing system with unreliable servers, discouraged customers and vacation. The model is explored with a view to reduce the impact of unreliable servers on the system performance. This is attained by providing regular maintenance to the servers through synchronised vacation. Further, the customer facing service interruption on account of server breakdown is directed to the orbit from where the customer can retry seeking service. In this study, the stationary system size distribution is framed by quasi-birth–death (QBD) process. The rate matrix and steady state probabilities are established using matrix geometric method (MGM). The performance measures are derived by using matrix form expressions. The effects induced by the system parameters on the performance metrics are numerically and graphically analysed. Through numerical investigation, we provide insightful information that enables to manage the system to give enhanced system performance.

Machine repair system with threshold recovery policy, unreliable servers and phase repairs

ABSTRACT This study aims to discuss queueing modeling of machine repair problems under threshold recovery policy (Q), server unreliability and k-type phase repairs. When one or more machines in the system fails/fail, the service facility (or all R -servers) is activated and repairs the failed machine according to the first come, first served (FCFS) discipline. The service facility may experience a partial or complete breakdown while providing service and needs to be repaired in required phases under the threshold recovery policy (Q). The matrix geometric approach is applied to solve the system governing equations, and a sensitivity analysis is presented to understand the effect of various parameters on system performance metrics. The greedy selection method and the golden section method are used to compute optimal rates of R ∗ , μ ∗ of service facility in order to minimize the cost function of the system.

Markovian Unreliable Server Retrial Queue with Double Orbit, Imperfect Repair and Balking

Markovian Unreliable Server Retrial Queue with Double Orbit, Imperfect Repair and Balking

Stability analysis of a two-class system with constant retrial rate and unreliable server

Stability analysis of a two-class system with constant retrial rate and unreliable server

Accuracy of Estimation of the Vector of Queue Lengths for Open Jackson Networks

The accuracy of approximation of the vector of queue lengths for an open Jackson network with regenerative input flow and unreliable servers is estimated. A theorem on the accuracy of approximation of the vector of queue lengths in open Jackson networks is put forward, i.e., an estimate for the probability of deviations of the norm of the difference between the process of queue lengths and the constructed reflected Brownian motion is obtained. As a corollary, an estimate of the Wasserstein distance is given.

Analysis of an unreliable server with soft failures and working vacations and its application in a smart healthcare system

The majority of the studies on queues with failing servers focused on catastrophic failures. Catastrophic failures are actually a particular kind of server failure that causes system clearing. Routine errors, unlike catastrophic failures, do not destroy the system; instead, all users must wait for the server to be activated again. In this study, with an application to a smart healthcare system, the analytical equations for the transient state probability of an unreliable server with soft failures and a working vacation are presented for the first time. The performance metrics are also developed. Numerical visuals are developed to support theoretical results.

Analysis of bulk service queuing system with rework, unreliable server, resuming service and two kinds of multiple vacation

In this paper, we discuss a batch arrival bulk service queue with rework for the faculty item, possibility of breakdown, repair, and two kinds of multiple vacation with different threshold policy. The server serves the remaining service after repair completion. This type of queuing model has a lot of applications in the manufacturing/ production industries. Performance measures and stability conditions are obtained. Numerical illustrations are made to examine the validity of analytical results.

A two server tandem queueing model with Markovian arrival process, phase type service, working vacation, feedback, re-service, unreliable server, interrupted closedown and customers intolerance.

A two server tandem queueing model with Markovian arrival process, phase type service, working vacation, feedback, re-service, unreliable server, interrupted closedown and customers intolerance.

Analysis of MAP/PH/1 Retrial Inventory Queueing System with Phase type Vacation and Unreliable Server

Analysis of MAP/PH/1 Retrial Inventory Queueing System with Phase type Vacation and Unreliable Server

Trust-Aware Scheduling for Edge Computing With Task Dependencies and Unreliable Servers

Trust-Aware Scheduling for Edge Computing With Task Dependencies and Unreliable Servers

Analysis of MAP/PH/1 Retrial queueing system with Two-stage vacations with imperfect service, N-policy service, Delayed feedback, Unreliable server and Discouragement customer

Analysis of MAP/PH/1 Retrial queueing system with Two-stage vacations with imperfect service, N-policy service, Delayed feedback, Unreliable server and Discouragement customer

Performance analysis for F-policy machine repair problem with unreliable server balking, working breakdown and retention

Performance analysis for F-policy machine repair problem with unreliable server balking, working breakdown and retention

Asymptotic waiting time analysis of finite source $M/GI/1$ retrial queueing systems with conflicts and unreliable server

Asymptotic waiting time analysis of finite source $M/GI/1$ retrial queueing systems with conflicts and unreliable server

Strategic access in a Green IoT(Internet of Things) system with an unreliable server

The present research aims to study the strategic behaviour of users in an Internet of Things(IoT) system that is impeded by an unreliable server. In the system, an IoT device is equipped with an energy harvesting unit. The IoT system under study is employed as a Markovian retrial queueing system that is used in a single server, subject to active failures. The failed server is repaired immediately, while the user who was served before the system’s breakdown event waits in the server until the server is repaired. The generating function approach is used to identify important system performance metrics. Moreover, queueing theory concepts are incorporated into game theory for the analysis of the users’ strategies. The users in the IoT system, act to maximize their expected benefit without being perturbed by other users in the system and determine their equilibrium joining strategies. Furthermore, taking into account social welfare factors, the IoT device acts as a social planner, and as a consequence, socially optimal joining strategies are also analysed. Finally, the analytical findings are validated with numerical examples.