We study the Task Assignment based on Guessing Size (TAGS) policy in a parallel and homogeneous server system. The policy parameters are the number of servers h and a set of cutoffs s1

A Markovian network of two queues, with finite size batch Poisson arrivals and departures, is solved approximately, but to arbitrary accuracy, for its equilibrium state probabilities. Below a pair of thresholds on the queue lengths, a modification of the Spectral Expansion Method is used to construct a semi-product-form at all lengths of one queue in a finite lattice strip defined by the threshold

Understanding workloads and modeling their performance is important for optimizing systems and services. A useful first step towards understanding the characteristics of workloads is to analyze their inter-arrival times and service requirements. If these characteristics are found to follow certain probability distributions, then corresponding stochastic models can be employed to efficiently estimate

We consider assignment policies that allocate resources to users, where both resources and users are located on a one-dimensional line [0,∞). First, we consider unidirectional assignment policies that allocate resources only to users located to their left. We propose the Move to Right (MTR) policy, which scans from left to right assigning nearest rightmost available resource to a user, and contrast

Compiler optimization passes employ cost models to determine if a code transformation will yield performance improvements. When this assessment is inaccurate, compilers apply transformations that are not beneficial, or refrain from applying ones that would have improved the code. We analyze the accuracy of the cost models used in LLVM’s and GCC’s vectorization passes for three different instruction

Loyalty programs are important tools for sharing platforms seeking to grow supply. Online sharing platforms use loyalty programs to heavily subsidize resource providers, encouraging participation and boosting supply. As the sharing economy has evolved and competition has increased, the design of loyalty programs has begun to play a crucial role in the pursuit of maximal revenue. In this paper, we first

A finite-buffer queueing system with threshold waking and early setup policy is investigated. The arrival stream is governed by a Poisson process while service times are assumed to be generally distributed. The natural FIFO processing discipline is used. Every time when the system empties, a type-specific energy saving policy is initialized that is a mixture of the classical N-type policy and an early

In this paper, a few models for optical router nodes are considered. The stations (ports) of such a node try to transmit packets. Successful transmission of a packet of type j at station i gives a profit γij, but there is also a positive probability that such a packet is dropped, causing a penalty θij. Consider one fixed cycle (frame), in which each station is assigned some visit time. The goal is

Large and unmanaged router buffers could lead to an increase in queuing delays in the Internet, which is a serious concern for network performance and quality of service. Our focus is to conduct a performance evaluation of Compound TCP (C-TCP), in a regime where the router buffer sizes are small (i.e., independent of the bandwidth-delay product), and the queue policy is Drop-Tail. In particular, we

As a multi-class variant of the classical egalitarian processor-sharing (EPS) discipline, discriminatory processor sharing (DPS) provides a suitable paradigm to model systems where share exists to control the service access of heterogeneous jobs. Although DPS is a more fine-grained scheduling discipline than EPS, the behavior of closed queueing networks (QNs) with DPS remains poorly understood. We

Storage is performance critical for I/O intensive applications deployed in data centers. As one of the recent implementations, media-based cache (MBC) is designed to alleviate the performance bottleneck of hard disk drives (HDD). This paper is motivated by the performance analysis of MBC in HDD and a new queueing model called M/G[b]/1/K with multiple state-dependent vacations is developed to formulate

We develop a unified framework for analyzing and optimizing costs for systems of FCFS queues with batch arrivals, setup delays and a general nonlinear cost structure that includes costs associated with energy used, setup times and Quality of Service (QoS) measures. We focus on the MX/G/1 and GeoX/G/1 queues with i.i.d. service times, but our results hold also for arbitrary i.i.d. batch structures where

Stability and diversity of end-to-end routes are key properties of Internet that have a large effect on the design of networks and networked systems. As the Internet evolves and deploys new technologies, it is important to re-assess these properties in the face of the new realities. This paper evaluates the stability and diversity of Internet routes with emphasis on the impact of the widely deployed

The paper revisits the performance evaluation of caching in a Named Data Networking (NDN) router where the content store (CS) is supplemented by a pending interest table (PIT). The PIT aggregates requests for a given content that arrive within the download delay and thus brings an additional reduction in upstream bandwidth usage beyond that due to CS hits. We extend prior work on caching with non-zero

In this paper, we consider an MX/M/1/GSET-VARI queue, which is a single server queue with a variable service speed, batch arrivals and general setup times. The service speed of the server is proportional to the number of jobs in the system. Our model is motivated by power-aware servers in data centers where dynamic scaling techniques are used. In this paper, we obtain the necessary and sufficient condition

This paper investigates the performance of the numerical inverse Laplace transformation (ILT) method based on concentrated matrix exponential (CME) distributions, referred to as the CME method. The CME method does not generate overshoot and undershoot (i.e., avoids Gibbs oscillation), preserves monotonicity of functions, its accuracy is gradually improving with the order, and it is numerically stable

We consider a resource allocation problem in a geographically distributed cloud network, where the goal is to obtain the capacities of the servers across the network in order to minimize the overall cost. In this study, the system resources (servers) are subject to failures, due to occasional breakdowns or cyber attacks. As a result, the servers supply is of a stochastic nature. From an optimization