Optimal Open-Loop Routing and Threshold-Based Allocation in TWO Parallel QUEUEING Systems with Heterogeneous Servers

In this paper, we study the problem of optimal routing for the pair of two-server heterogeneous queues operating in parallel and subsequent optimal allocation of customers between the servers in each queue. Heterogeneity implies different servers in terms of speed of service. An open-loop control assumes the static resource allocation when a router has no information about the state of the system. We discuss here the algorithm to calculate the optimal routing policy based on specially constructed Markov-modulated Poisson processes. As an alternative static policy, we consider an optimal Bernoulli splitting which prescribes the optimal allocation probabilities. Then, we show that the optimal allocation policy between the servers within each queue is of threshold type with threshold levels depending on the queue length and phase of an arrival process. This dependence can be neglected by using a heuristic threshold policy. A number of illustrative examples show interesting properties of the systems operating under the introduced policies and their performance characteristics.

Stability of Parallel Server Systems

A parallel server system is a queueing system in which jobs are routed upon their arrivals to one of several buffers, each handled by a different server. The main operational and theoretical problem in such systems is to find an efficient routing policy that maximizes their throughput (or minimizes waiting times). The paper “Stability of Parallel Server Systems” considers a large class of routing policies, which includes the most prevalent policies studies in the literature, under the assumption that routing errors may occur because ofincomplete information about the state of the system at decision epochs. The stability region for this class of policies is studied as a function of the error probability, and it is shown that the standard stability condition, namely, that the traffic intensity is smaller than one, does not guarantee that the system is stable.

Minimizing Mean Response Time In Batch-Arrival Non-Observable Systems With Single-Server FIFO Queues Operating In Parallel

Consideration is given to a dispatching system, where jobs, arriving in batches, cannot be stored and thus must be immediately routed to single-server FIFO queues operating in parallel. The dispatcher can memorize its routing decisions but at any time instant does not have any system's state information. The only information available is the batch/job size and inter-arrival time distributions, and the servers' service rates. Under these conditions, one is interested in the routing policies which minimize the job's long-run mean response time. The single-parameter routing policy is being proposed which, according to the numerical experiments, outperforms best routing rules known by now for non-observable dispatching systems: probabilistic and deterministic. Both the batch-wise and job-wise assignments are studied. Extension to systems with unreliable servers is also addressed.

An Enhanced routing Technique to improve the Network Lifetime of Cognitive Sensor Network

In terms of using the technology of Cognitive Radio (CR), a Cognitive Sensor Network (CSN) is varied from the conventional Wireless Sensor Networks (WSNs). According to the interaction with the surrounding environment, the transmitter parameters can be modified in the sensor nodes of CSN adaptively. In CSNs, routing is one of the important components. Based on the capability of spectrum-aware, the schemes of routing of CSNs are district from other networks. The changeable spectrum resource dynamically should be understood by the routing scheme to establish a path of reliable forwarding by the adjustment of routing policy adaptively. In CSNs, reliable routing is an essential thing but still not a well-explored problem in CSNs. Packet drops due to spectrum unavailability and buffer overflows seriously affects the connectivity of the nodes. The whole network’s lifetime and the data delivery rate are impacted by the prolonging packet drops. To increase the nodes’ lifetime, the addressing of this drawback in the phase of routing should be done. Before the making of routing decisions, a new routing technique is proposed named as Drop factor based energy efficient routing technique (DFBEER) with the use of packet drop ratio and power dissipation metric of the spectrum links. With the total number of users in the routing path, the drop factor is computed. Power dissipation is calculated based on the transmitted data packets versus the amount of total consumed energy. This method reduces the drop ratio by avoiding the high drop factor nodes from being participating in the routing process. It always ensures that the data would be handled by the low dropping ratio nodes, thus the network’s lifetime is improved.

Improved Dynamic Routing Algorithm for Information Aggregation

Information aggregation is an essential component of text encoding, but it has been paid less attention. The pooling-based (max or average pooling) aggregation method is a bottom-up and passive aggregation method, and loses a lot of important information. Recently, attention mechanism and dynamic routing policy are separately used to aggregate information, but their aggregation capabilities can be further improved. In this paper, we proposed an novel aggregation method combining attention mechanism and dynamic routing, which can strengthen the ability of information aggregation and improve the quality of text encoding. Then, a novel Leaky Natural Logarithm (LNL) squash function is designed to alleviate the “saturation” problem of the squash function of the original dynamic routing. Layer Normalization is added to the dynamic routing policy for speeding up routing convergence as well. A series of experiments are conducted on five text classification benchmarks. Experimental results show that our method outperforms other aggregating methods.