Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains. Primarily, this is due to the explosion in the availability of data, significant improvements in ML techniques, and advancement in computing capabilities. Undoubtedly, ML has been applied to various mundane and complex problems arising in network operation and management. There are various surveys on ML for specific areas in networking or for specific network technologies. This survey is original, since it jointly presents the application of diverse ML techniques in various key areas of networking across different network technologies. In this way, readers will benefit from a comprehensive discussion on the different learning paradigms and ML techniques applied to fundamental problems in networking, including traffic prediction, routing and classification, congestion control, resource and fault management, QoS and QoE management, and network security. Furthermore, this survey delineates the limitations, give insights, research challenges and future opportunities to advance ML in networking. Therefore, this is a timely contribution of the implications of ML for networking, that is pushing the barriers of autonomic network operation and management.

/pdf/a-comprehensive-survey-on-machine-learning-for-networking-3t5h3kbpe8.pdf

A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

In this article, we introduce an Internet of Things application, smart community, which refers to a paradigmatic class of cyber-physical systems with cooperating objects (i.e., networked smart homes). We then define the smart community architecture, and describe how to realize secure and robust networking among individual homes. We present two smart community applications, Neighborhood Watch and Pervasive Healthcare, with supporting techniques and associated challenges, and envision a few value-added smart community services.

/pdf/smart-community-an-internet-of-things-application-4wxc9hcbvb.pdf

Smart community: an internet of things application

The Internet Protocol.

The Internet provides a platform for rapid and timely information exchange among a disparate array of clients and servers. TCP and IP are separately designed and closely tied protocols that define the rules of communication between end hosts, and are the most commonly used protocol suite for data transfer in the Internet. The combination of TCP/IP dominates today's communication in various networks from the wired backbone to the heterogeneous network due to its remarkable simplicity and reliability, TCP has become the de facto standard used in most applications ranging from interactive sessions such as Telnet and HTTP, to bulk data transfer like FTP. TCP was originally designed primarily for wired networks. In a wired network, random bit error rate, a characteristic usually more pronounced in the wireless network, is negligible, and congestion is the main cause of packet loss. The emerging wireless applications, especially high-speed multimedia services and the advent of wireless IP communications carried by the Internet, call for calibration and sophisticated enhancement or modifications of this protocol suite for improved performance. Based on the assumption that packet losses are signals of network congestion, the additive increase multiplicative decrease congestion control of the standard TCP protocol reaches the steady state, which reflects the protocol's efficiency in terms of throughput and link utilization. However, this assumption does not hold when the end-to-end path also includes wireless links. Factors such as high BER, unstable channel characteristics, and user mobility may all contribute to packet losses. Many studies have shown that the unmodified standard TCP performs poorly in a wireless environment due to its inability to distinguish packet losses caused by network congestion from those attributed to transmission errors. In this article, following a brief introduction to TCP, we analyze the problems TCP exhibits in the wireless IP communication environment, and illustrate viable solutions by detailed examples.

/pdf/tcp-in-wireless-environments-problems-and-solutions-yzljtaah4d.pdf

TCP in wireless environments: problems and solutions

The present electric power system structure has lasted for decades; it is still partially proprietary, energy-inefficient, physically and virtually (or cyber) insecure, as well as prone to power transmission congestion and consequent failures. Recent efforts in building a smart grid system have focused on addressing the problems of global warming effects, rising energy-hungry demands, and risks of peak loads. One of the major goals of the new system is to effectively regulate energy usage by utilizing the backbone of the prospectively deployed Automatic Meter Reading (AMR), Advanced Meter Infrastructure (AMI), and Demand Response (DR) programs via the advanced distribution automation and dynamic pricing models. The function of the power grid is no longer a system that only supplies energy to end users, but also allows consumers to contribute their clean energy back to the grid in the future. In the meantime, communications networks in the electric power infrastructure enact critical roles. Intelligent automation proposed in smart grid projects include the Supervisory Control And Data Acquisition/Energy Management Systems (SCADA/EMS) and Phasor Management Units (PMU) in transmission networks, as well as the AMR/AMI associated with field/neighborhood area networks (FAN/NAN) and home area networks (HAN) at the distribution and end-use levels. This article provides an overview of the essentials of the progressive smart grid paradigm and integration of different communications technologies for the legacy power system. Additionally, foreseeable issues and challenges in designing communications networks for the smart grid system are also rigorously deliberated in this paper.

/pdf/the-progressive-smart-grid-system-from-both-power-and-7oc2736nf1.pdf

The Progressive Smart Grid System from Both Power and Communications Aspects

https://web.njit.edu/~ansari/papers/05ComNet_Xu.pdf

Improving TCP performance in integrated wireless communications networks

Proportional fair queuing is to ensure that a flow passing through the network only consumes a fair share of the network resource that is proportional to its committed rate or other service level agreement (SLA). It is of great importance in Differentiated Services (DiffServ) networks as well as other price incentive network services. In this paper, we propose a simple core-stateless proportional fair queuing algorithm (CSPFQ) for the assured forward (AF) traffic in DiffServ networks. We first develop our algorithm based on a fluid model analysis and then extend it to a realizable packet level algorithm. We prove analytically and instantiate through simulations that our algorithm can achieve proportional fair bandwidth allocation among competing flows without requiring routers to estimate flows' fair share rates. Our simulation results also demonstrate that our algorithm outperforms the weighted core-stateless fair queuing (WC-SFQ) in terms of proportional fairness.

/pdf/core-stateless-proportional-fair-queuing-for-af-traffic-3n0m8d8hga.pdf

Core-stateless proportional fair queuing for AF traffic

Sharing a resource may include the use of label values associated with information units presented to the resource. The label values may be determined based on, for example, arrival rates and/or committed flow rates. Criteria may be applied to label values to determine if the associated information units may be dropped.

Providing Proportionally Fair Bandwidth Allocation in Communication Systems

The transmission control protocol (TCP) exhibits poor performance when used in error-prone wireless networks. Remedy to this problem has been an active research area. However, a widely accepted and adopted solution is yet to emerge. Difficulties of an acceptable solution lie in the areas of compatibility, scalability, computational complexity, and the involvement of intermediate routers and switches.
This dissertation reviews the current start-of-the-art solutions to TCP performance enhancement, and pursues an end-to-end solution framework to the problem. The most noticeable cause of the performance degradation of TCP in wireless networks is the higher packet loss rate as compared to that in traditional wired networks. Packet loss type differentiation has been the focus of many proposed TCP performance enhancement schemes. Studies conduced by this dissertation research suggest that besides the standard TCP's inability of discriminating congestion packet losses from losses related to wireless link errors, the standard TCP's additive increase and multiplicative decrease (AIMD) congestion control algorithm itself needs to be redesigned to achieve better performance in wireless, and particularly, high-speed wireless networks. This dissertation proposes a simple, efficient, and effective end-to-end solution framework that enhances TCP's performance through techniques of adaptive congestion control and active queue management. By end-to-end, it means a solution with no requirement of routers being “wireless-aware” or “wireless-specific”. 
TCP-Jersey has been introduced as an implementation of the proposed solution framework, and its performance metrics have been evaluated through extensive simulations. TCP-Jersey consists of an adaptive congestion control algorithm at the source by means of the source's achievable rate estimation (ARE)—an adaptive filter of packet inter-arrival times, a congestion indication algorithm at the links (i.e., AQM) by means of packet marking, and a effective loss differentiation algorithm at the source by careful examination of the congestion marks carried by the duplicate acknowledgment packets (DUPACK).
Several improvements to the proposed TCP-Jersey have been investigated, including a more robust ARE algorithm, a less computationally intensive threshold marking algorithm as the AQM link algorithm, a more stable congestion indication function based on virtual capacity at the link, and performance results have been presented and analyzed via extensive simulations of various network configurations. Stability analysis of the proposed ARE-based additive increase and adaptive decrease (AIAD) congestion control algorithm has been conducted and the analytical results have been verified by simulations. Performance of TCP-Jersey has been compared to that of a “perfect”, but not practical, TCP scheme, and encouraging results have been observed. Finally, the framework of the TCP-Jersey's source algorithm has been extended and generalized for rate-based congestion control, as opposed to TCP's window-based congestion control, to provide a design platform for applications, such as real-time multimedia, that do not use TCP as transport protocol yet do need to control network congestion as well as combat packet losses in wireless networks.
In conclusion, the framework architecture presented in this dissertation that combines the adaptive congestion control and active queue management in solving the TCP performance degradation problem in wireless networks has been shown as a promising answer to the problem due to its simplistic design philosophy, complete compatibility with the current TCP/IP and AQM practice, end-to-end architecture for scalability, and the high effectiveness and low computational overhead. The proposed implementation of the solution framework, namely, TCP-Jersey, is a modification of the standard TCP protocol rather than a completely new design of the transport protocol. It is an end-to-end approach to address the performance degradation problem since it does not require split mode connection establishment and maintenance using special wireless-aware software agents at the routers. The proposed solution also differs from other solutions that rely on the link layer error notifications for packet loss differentiation.
The proposed solution is also unique among other proposed end-to-end solutions in that it differentiates packet losses attributed to wireless link errors from congestion induced packet losses directly from the explicit congestion indication marks in the DUPACK packets, rather than inferring the loss type based on packet delay or delay jitter as in many other proposed solutions; nor by undergoing a computationally expensive off-line training of a classification model (e.g., HMM), or a Bayesian estimation/detection process that requires estimations of a priori loss probability distributions of different loss types.
The proposed solution is also scalable and fully compatible to the current practice in Internet congestion control and queue management, but with an additional function of loss type differentiation that effectively enhances TCP's performance over error-prone wireless networks.
Limitations of the proposed solution architecture and areas for future researches are also addressed.

Tcp performance enhancement in wireless networks via adaptive congestion control and active queue management

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