An Efficient Routing Implementation for Irregular Networks

with the recent advancements in multi-core era workstation clusters have emerged as a cost-effective approach to build a network of workstations NOWs NOWs connect the small groups of processors to a network of switching elements that form irregular topologies Designing an efficient routing and a deadlock avoidance algorithm for irregular networks is quite complicated in terms of latency and area of the routing tables thus impractical for scalability of On Chip Networks Many deadlock free routing mechanisms have been proposed for regular networks but they cannot be employed in irregular networks In this paper a new methodology has been proposed for efficient routing scheme called LBDR-UD which save the average 64 59 routing tables in the switch for irregular networks as compare to up down routing The Basic concept of routing scheme is combination of up down and Logic Based Distributed Routing By simulation it has been shown that the LBDR-UD is deadlock free and adaptive to all dynamic network traffic condition

Reliable Resource Provisioning using Bankers’ Deadlock Avoidance Algorithm in MEC for Industrial IoT

Multi-Access Edge Computing (MEC) is a new 5G enabling technology proposed to reduce latency by bringing cloud computing capability closer to IoT and mobile device users. MEC may be prone to unreliable communication as a result of deadlock during resource provisioning. Deadlock may occur due to a huge number of devices contending for a limited amount of resources if adequate measures are not put in place. It is crucial to eradicate deadlock while scheduling and provisioning of resources on MEC to achieve highly reliable and available system. In this paper, a deadlock avoidance resource provisioning algorithm is proposed for Industrial IoT devices using MEC platforms to ensure higher reliability of network interactions. The proposed scheme incorporates banker’s resource-request algorithm using SDN to reduce communication overhead. Simulation Results have shown that system deadlock can be prevented by applying the proposed algorithm which ultimately leads to a more reliable network interaction between mobile stations and MEC platforms

Parallel discrete event simulation: A shared memory approach

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models

Simulation Study of a Semi-Dynamic AGV-Container Unit Job Deployment Scheme

Automated Guided Vehicle (AGV) Container-Job deployment is essentially a vehicle-dispatching problem. In this problem, the impact of vehicle dispatching polices on the ship makespan for discharging and/or loading operations is analyzed. In particular, given a storage location for each container to be discharged from the ship and given the current location of each container to be loaded onto the ship, the problem is to propose an efficient deployment scheme to dispatch vehicles to containers so as to minimize the makespan of the ship so as to increase the throughput. The makespan of the ship refers to the time a ship spends at the port for loading and unloading operations. In this paper, we will compare the performance of current deployment scheme used with the new proposed deployment scheme, both with deadlock prediction & avoidance algorithm done in previous study [1]. The prediction & avoidance algorithm predicts and avoids cyclic deadlock. The current deployment scheme, namely pmds makes use of a greedy heuristics which dispatches the available vehicle that will reach the quay with the minimum amount of time the vehicle has to spend waiting for the crane to discharge/load the container from/onto the ship. The new deployment scheme, namely mcf aims to formulate the problem as a minimum cost flow problem, which will then be solved by network simplex code. The two simulation models are implemented using discrete-event simulation software, AutoMod, and the performances of both deployment schemes are analyzed. The simulation results show that the new deployment scheme will result in a higher throughput and lower ship makespan than the current deployment scheme.Singapore-MIT Alliance (SMA