NetSE: Small: Delay Minimization in Wireless Networks

NetSE：小型：无线网络中的延迟最小化

• 批准号: 1018185
• 负责人: Sennur Ulukus
• 金额: $ 25.03万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1018185&HistoricalAwards=false
• 关键词: NetSE; Small; Delay; Minimization; Wireless

Traditional information theory investigates transmission problems from a physical layer perspective. Information theory aims to determine largest achievable communication rates between transmitters and receivers for a given physical communication channel. In the simplified source-channel-destination model, information-theoretic approaches assume the availability of an infinite number of bits at the transmitters before the transmission starts. The burstiness of the arrivals and the associated issue of delay are mostly ignored. In contrast, network theory gives sophisticated analysis of network layer issues, such as random arrivals and network delay. However, in network-theoretic approaches, the underlying physical layer model is usually very simplified, e.g., in most approaches simultaneous transmissions are not allowed, and even when they are allowed, a collision channel model is used, which is far too simplistic to capture what can be achieved in the physical layer from an information-theoretic perspective.This project aims to develop a fundamental understanding for the issue of delay in networks, and design transmission methods and scheduling algorithms to minimize delay in network communications. Towards this goal, this project combines techniques from information theory, network theory, queueing theory and optimization theory. The investigators use information-theoretic techniques to improve the underlying information carrying rates, together with queueing- and network-theoretic tools to allocate these rates to network users considering external arrival rates and current queue sizes. Further, the investigators incorporate physical layer phenomena such as fading (enabling opportunistic transmissions) and overheard information (enabling cooperation) into this development. In addition, in networking applications where nodes are able to harvest energy from nature, the investigators consider the interactions between the random packet arrivals and the random energy arrivals (through harvesting) to nodes, in designing the transmission and scheduling mechanisms.

传统的信息理论从物理层的角度研究传输问题。信息论的目的是确定发射机和接收机之间的最大可实现的通信速率为一个给定的物理通信信道。在简化的源-信道-目的地模型中，信息论方法假设在传输开始之前在发射机处有无限数量的比特可用。到达的突发性和相关的延迟问题大多被忽略。相比之下，网络理论对网络层问题进行了复杂的分析，例如随机到达和网络延迟。然而，在网络理论方法中，底层物理层模型通常非常简化，例如，在大多数方法中，不允许同时传输，即使允许同时传输，也使用冲突信道模型，该模型过于简单，无法从信息论的角度捕获在物理层中可以实现的内容。本项目旨在对网络中的延迟问题有基本的理解，并设计传输方法和调度算法，以最大限度地减少网络通信中的延迟。为此，本课题综合运用了信息论、网络论、决策论和最优化理论等技术。调查人员使用信息理论的技术，以提高基本的信息携带率，与网络理论工具，以分配这些速率给网络用户考虑外部到达率和当前队列大小。此外，研究人员将物理层现象，如衰落（使机会传输）和偷听到的信息（使合作）到这一发展。此外，在网络应用中，节点能够从自然界中收获能量，研究人员在设计传输和调度机制时考虑了随机数据包到达节点和随机能量到达节点（通过收获）之间的相互作用。