Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals

We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound

A Credit-based Home Access Point (CHAP) to Improve Application Quality on IEEE 802.11 Networks

Increasing availability of high-speed Internet and wireless access points has allowed home users to connect not only their computers but various other devices to the Internet. Every device running different applications requires unique Quality of Service (QoS). It has been shown that delay- sensitive applications, such as VoIP, remote login and online game sessions, suffer increased latency in the presence of throughput-sensitive applications such as FTP and P2P. Currently, there is no mechanism at the wireless AP to mitigate these effects except explicitly classifying the traffic based on port numbers or host IP addresses. We propose CHAP, a credit-based queue management technique, to eliminate the explicit configuration process and dynamically adjust the priority of all the flows from different devices to match their QoS requirements and wireless conditions to improve application quality in home networks. An analytical model is used to analyze the interaction between flows and credits and resulting queueing delays for packets. CHAP is evaluated using Network Simulator (NS2) under a wide range of conditions against First-In-First- Out (FIFO) and Strict Priority Queue (SPQ) scheduling algorithms. CHAP improves the quality of an online game, a VoIP session, a video streaming session, and a Web browsing activity by 20%, 3%, 93%, and 51%, respectively, compared to FIFO in the presence of an FTP download. CHAP provides these improvements similar to SPQ without an explicit classification of flows and a pre- configured scheduling policy. A Linux implementation of CHAP is used to evaluate its performance in a real residential network against FIFO. CHAP reduces the web response time by up to 85% compared to FIFO in the presence of a bulk file download. Our contributions include an analytic model for the credit-based queue management, simulation, and implementation of CHAP, which provides QoS with minimal configuration at the AP

Application of learning algorithms to traffic management in integrated services networks.

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