The Knowledge of Bandwidth in Communication Network (Other (Not Listed) Sample)

Through the Diversity of Bandwidth-Related Metrics, Estimation Techniques and Tools: An Overview
Fatih Abut
Adana Science and Technology University, Dept. of Computer Engineering, Adana, 01250, Turkey
Email: fabut@adanabtu.edu.tr
Abstract— The knowledge of bandwidth in communication networks can be useful in various applications. Some popular examples are validation of service level agreements, traffic engineering and capacity planning support, detection of congested or underutilized links, optimization of network route selection, dynamic server selection for downloads and visualizing network topologies, to name just a few. Following these various motivations, a variety of bandwidth estimation techniques and tools have been proposed in the last decade and still, several new ones are currently being introduced. They all show a wide spectrum of different assumptions, characteristics, advantages and limitations. In this paper, the bandwidth estimation literature is reviewed, with focus on introducing four specific bandwidth-related metrics including capacity, available bandwidth, achievable throughput and bulk transfer capacity (BTC); describing the main characteristics, strengths and weaknesses of major bandwidth estimation techniques as well as classifying the respective tool implementations. Also, the fundamental challenges, practical issues and difficulties faced by designing and implementing bandwidth estimation techniques are addressed.
Index Terms— Capacity, Available Bandwidth, Throughput, Estimation Techniques, Active Probing, Quality of Service.
I. Introduction
Bandwidth has been a critical and precious resource in various kinds of networks. Having a good estimate of bandwidth is, for example, important for network error detection and diagnosis as well as for efficient operation of bandwidth dependent/data-intensive Internet applications. Some popular examples where knowledge of bandwidth can be valuable are validation of service level agreements, detection of congested or underutilized links and capacity planning support, admission control policies at massively-accessed content servers, network tomography for tracking and visualizing Internet topology, dynamic server selection for downloads, optimized congestion control for reliable transport protocols (e.g. for TCP) and optimized network route selection.
Figure 1 shows an overview of major bandwidth estimation techniques and tools. They mainly estimate one of three related metrics: capacity, available bandwidth and throughput. The latter can, in turn, be divided into achievable throughput and bulk transfer capacity (BTC). The estimation of each metric is associated at least with one estimation technique whereas one and the same metric can also be estimated with several and independentestimation techniques in different ways. Representative examples of estimation techniques used by different estimation tools range from Packet Pair (PP) and Variable Packet Size (VPS) estimating the end-to-end and hop-by-hop capacity, respectively, to Probe Rate Model (PRM) and Probe Gap Model (PGM) estimating the end-to-end available bandwidth to TCP connections or emulations used for measuring end-to-end achievable throughput and BTC metrics. Estimation techniques shown in Figure 1 are represented by several various tool implementations. They all show a wide spectrum of different assumptions, characteristics, advantages and limitations:
* Active vs. passive estimation tools
* Intrusive vs. lightweight estimation tools
* Single-ended vs. double-ended estimation tools
* Offline vs. online (or real-time) estimation tools
* Ability to measure asymmetric, wireless or high-speed links
* Different levels of achievable estimation accuracy
* Differences in estimation time needed and probing overhead caused
From the point of a user’s view, the wishing list for an ideal estimation technique and tool is long and manifold, and includes requirements such as accurate, consistent and reliable estimates; low overhead, fast and robust estimation procedures; resilience to both cross traffic and its rapid changing conditions; independence of the measurement end-host performance and system capabilities; and finally, applicability to mixed paths consisting of wired, high-speed and/or wireless links.
Current estimation techniques and tools mainly suffer from two categories of challenges that lead to unstable and inaccurate estimates: Challenges that exists in Internet environment such as route alternations, multi-channel and asymmetric links, multiple existing bottlenecks, traffic shapers or network components working with non-FIFO queuing disciplines; or challenges which are related to end-hosts performing the measurements such as interrupt coalescence, limited system I/O capability, limited system timer resolution, context switching and clock skew.
The purpose of this paper is (a) to introduce specific bandwidth-related metrics, highlighting the scope and relevance of each; (b) to describe the rationales of the major existing bandwidth estimation techniques; and (c) to survey and uniformly classify the various existing -6240358Fig. 1. An Overview: Metrics, Techniques and Tools00Fig. 1. An Overview: Metrics, Techniques and Toolsbandwidth estimation tools. Differently from the rest of survey studies in literature ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1109/MNET.2003.1248658","ISBN":"2075946302","ISSN":"0890-8044","abstract":"In a packet network, the terms bandwidth and throughput often characterize the amount of data that the network can transfer per unit of time. Bandwidth estimation is of interest to users wishing to optimize end-to-end transport performance, overlay network routing, and peer-to-peer file distribution. Techniques for accurate bandwidth estimation are also important for traffic engineering and capacity planning support. Existing bandwidth estimation tools measure one or more of three related metrics: capacity, available bandwidth, and bulk transfer capacity. Currently available bandwidth estimation tools employ a variety of strategies to measure these metrics. In this survey we review the recent bandwidth estimation literature focusing on underlying techniques and methodologies as well as open source bandwidth measurement tools.","author":[{"dropping-particle":"","family":"Prosad","given":"R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Davrolis","given":"C.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Murray","given":"Margaret","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Claffy","given":"K.C. C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Prasad","given":"Ravi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dovrolis","given":"Constantinos","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Murray","given":"Margaret","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Claffy","given":"K.C. C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Association","given":"Cooperative","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Analysis","given":"Data","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"IEEE Network","id":"ITEM-1","issue":"6","issued":{"date-parts":[["2003"]]},"page":"27-35","title":"Bandwidth estimation: metrics, measurement techniques, and tools","type":"article-journal","volume":"17"},"uris":["http://www.mendeley.com/documents/?uuid=e378d644-90da-4382-a3f0-b5158c3d69f3"]},{"id":"ITEM-2","itemData":{"DOI":"10.1016/j.comcom.2009.08.010","ISSN":"01403664","abstract":"Available Bandwidth Estimation Techniques and Tools (ABETTs) have recently been envisioned as a supporting mechanism in areas such as compliance of service level agreements, network management, traffic engineering and real-time resource provisioning, flow and congestion control, construction of overlay networks, fast detection of failures and network attacks, and admission control. However, it is unknown whether current ABETTs can run efficiently in any type of network, under different network conditions, and whether they can provide available bandwidth estimates at the timescales needed by these applications. This article includes a performance evaluation of Pathload, Pathchirp, Spruce, IGI, and Abing in a low cost and flexible test bed. The evaluation includes scenarios and conditions not evaluated before, such as varying the packet loss rate and the propagation delays of the links, the amount of cross-traffic, the capacity of the links, and the cross-traffic packet size. The results demonstrate that ABETTs are far from being ready to be applied in all these applications and scenarios. In addition, the article clearly indicates those aspects that need further research and which ABETTs are the best candidates for specific applications and environments.","author":[{"dropping-particle":"","family":"Guerrero","given":"Cesar D.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Labrador","given":"Miguel A.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Computer Communications","id":"ITEM-2","issue":"1","issued":{"date-parts":[["2010"]]},"page":"11-22","title":"On the applicability of available bandwidth estimation techniques and tools","type":"article-journal","volume":"33"},"uris":["http://www.mendeley.com/documents/?uuid=52fa...