Pre-emptive Channel Borrowing and Traffic Overflowing Channel Allocation Scheme for Multimedia Overlay Networks

This paper proposes a channel allocation scheme for multimedia wireless networks,in which a twolayer macro-cell or micro-cell architecture is considered.Macro-cells are used to access high-mobility services;while micro-cells,which are overlaid by the macro-cells,are used to cater low-mobility services.To analyze the scheme,a multidimensional Markov traffic model is firstly developed,in which traffic characteristic of two special periods of time is considered.And then,a pre-emptive channel-borrowing scheme combined with trafficoverflowing strategy for multimedia(voice,video or data) networks is proposed,in which handoff requests can not only borrow channels from adjacent homogenous cells,but also be overflowed to heterogeneous cells.Priority strategies are also dedicated to high-mobility services for they can pre-empt channels being used by low-mobility services in macro-cells.To meet the high quality of service(QoS) requirements of video services and increase the channel utilization ratio,video services can be transformed between real-time services and non-real-time services as necessary.Simulation results show that our schemes can decrease the blocking probabilities and improve the channel utilization.

Machine Learning-based Stable P2P IPTV Overlay

Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service providers.Since Internet was not designed for such services during its inception,such a service poses some serious challenges including cost and scalability.Peer-to-Peer(P2P)Internet Protocol Television(IPTV)is an application-level distributed paradigm to offer live video contents.In terms of ease of deployment,it has emerged as a serious alternative to client server,Content Delivery Network(CDN)and IP multicast solutions.Nevertheless,P2P approach has struggled to provide the desired streaming quality due to a number of issues.Stability of peers in a network is one of themajor issues among these.Most of the existing approaches address this issue through older-stable principle.This paper first extensively investigates the older-stable principle to observe its validity in different scenarios.It is observed that the older-stable principle does not hold in several of them.Then,it utilizes machine learning approach to predict the stability of peers.This work evaluates the accuracy of severalmachine learning algorithms over the prediction of stability,where the Gradient Boosting Regressor(GBR)out-performs other algorithms.Finally,this work presents a proof-of-concept simulation to compare the effectiveness of older-stable rule and machine learning-based predictions for the stabilization of the overlay.The results indicate that machine learning-based stability estimation significantly improves the system.

Generation of Low-Delay and High-Stability Multicast Tree

Delay and stability are two key factors that affect the performance of multicast data transmission in a network.However,current algorithms of tree generation hardly meet the requirements of low delay and high sta-bility simultaneously.Given a general network,the generation algorithm of a multicast tree with minimum delay and maximum stability is an NP-hard problem,without a precise and efficient algorithm.To address these challenges,this paper studies the generation of low-delay and high-stability multicast trees under the model of spanning tree based on stability probability,degree-constrained,edge-weighted for multicast(T-SDE).A class of algorithms was proposed which creates the multicast tree greedy on the ratio of fan-out to delay(RFD)and probability of stability of terminal to obtain a high performance in multicast.The proposed algorithms greedily select terminals with a large RFD and a high probability of stability as forwarding nodes in the generation of the multicast tree,where the larger RFD and higher stability of upstream nodes are beneficial to achieve a low transmission delay and high stability in multicast.The proposed RFD can be compatible with the original model,which can take advantage of network connectivity during the generation of a multicast tree.This paper carries out simulation experiments on Matlab R2016b to measure the performance of the proposed algorithm.Experimental results show that the proposed algorithm can provide a smaller height,higher stability,and a lower transmission delay of the resulting multicast tree than other solutions.The spanning tree of the proposed algorithms can support low transmission delay and high stability in multicast transmission.

Virtualizing Network and Service Functions: Impact on ICT Transformation and Standardization

Virtualization of network/service functions means time sharing network/service（and affiliated）resources in a hyper speed manner.The concept of time sharing was popularized in the 1970s with mainframe computing.The same concept has recently resurfaced under the guise of cloud computing and virtualized computing.Although cloud computing was originally used in IT for server virtualization,the ICT industry is taking a new look at virtualization.This paradigm shift is shaking up the computing,storage,networking,and ser vice industries.The hope is that virtualizing and automating configuration and service management/orchestration will save both capes and opex for network transformation.A complimentary trend is the separation（over an open interface）of control and transmission.This is commonly referred to as software defined networking（SDN）.This paper reviews trends in network/service functions,efforts to standardize these functions,and required management and orchestration.

Closer:Scalable Load Balancing Mechanism for Cloud Datacenters

Cloud providers(e.g.,Google,Alibaba,Amazon)own large-scale datacenter networks that comprise thousands of switches and links.A loadbalancing mechanism is supposed to effectively utilize the bisection bandwidth.Both Equal-Cost Multi-Path(ECMP),the canonical solution in practice,and alternatives come with performance limitations or significant deployment challenges.In this work,we propose Closer,a scalable load balancing mechanism for cloud datacenters.Closer complies with the evaluation of technology including the deployment of Clos-based topologies,overlays for network virtualization,and virtual machine(VM)clusters.We decouple the system into centralized route calculation and distributed route decision to guarantee its flexibility and stability in large-scale networks.Leveraging In-band Network Telemetry(INT)to obtain precise link state information,a simple but efficient algorithm implements a weighted ECMP at the edge of fabric,which enables Closer to proactively map the flows to the appropriate path and avoid the excessive congestion of a single link.Closer achieves 2 to 7 times better flow completion time(FCT)at 70%network load than existing schemes that work with same hardware environment.

Providing Delay-Guaranteed Multicast Transmission Services for an SDN-Based Publish/Subscribe System

Providing end-to-end delay guarantees in traditional Internet is a complex task due to the distributed nature of TCP/IP protocols. Software Defined Networking(SDN) gives a new dimension to improve QoS(Quality of Service) as it can benefit from its flexibility, programmability and centralized view. In this paper, we provide delay-guaranteed data transmission service instead of "best efforts" service for a topic-based publish/subscribe system by means of exploring these specific features of SDN. We attribute this routing problem in such conditions to Delay-Constraint Lowest Cost Steiner Tree(DCLCST) problem. To solve it, we compute the shortest delay paths from source node to every subscribe node and the shortest cost paths from every subscribe node to any other node using dijkstra algorithm. Then we construct a delay-constraint least cost steiner tree for per-topic based on these paths as multicast tree. We also present experimental results to demonstrate the effectiveness of the algorithms and methods we proposed.

Network Function Virtualization Technology:Progress and Standardization

Network innovation and business transformation are both necessary for telecom operators to adapt to new situations, but operators face challenges in terms of network bearer complexity, business centralization, and IT/CT integration. Network function virtualization （NFV） may inspire new development ideas, but many doubts still exist within industry, especially about how to introduce NFV into an operator＇ s network. This article describes the latest progress in NFV standardization, NFV requirements and hot technology issues, and typical NFV applications in an operator networks.

Topology-aware peer-to-peer overlay network for Ad-hoc

The mismatch between the structured peer-to-peer （P2P） overlay network, which is based on Hashing, and the actual physical network, leads to query repeatedly passing through some nodes in the actual route when it is applied in Ad-hoc networks. An approach of getting an appropriate node identifier （ID） bearing its local physical information is proposed, in which the traditional theory of getting node ID through Hashing the node＇s Internet protocol （IP） address is abandoned, and a topology-aware overlay network suiting Ad-hoc networks is constructed. The simulation results show that the overlay network constructed in the proposed method can avoid the route being iteratively accessed. Meanwhile, it can effectively minimize the latency and improve the load balance.

Cloud Computing-Based Forensic Analysis for Collaborative Network Security Management System

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.

Publish/subscribe based information dissemination over VANET utilizing DHT

A vehicular ad-hoc network （VANET） can be visualized as a network of moving vehicles communicating in an asynchronous and autonomous fashion. Efficient and scalable information dissemination in VANET applications is a major challenge due to the movement of vehicles which causes unpredictable changes in network topology. The publish/subscribe communication paradigm provides decoupling in time, space, and synchronization between communicating entities, and presents itself as an elegant solution for information dissemination for VANET like environments. In this paper, we propose our approach for information dissemination which utilizes publish/subscribe and distributed hash table （DHT） based overlay networks. In our approach, we assume a hybrid VANET consisting of stationary info-stations and moving vehicles. These info-stations are installed at every major intersection of the city and vehicles can take the role of publisher, subscriber, or broker depending upon the context. The info-stations form a DHT based broker overlay among themselves and act as rendezvous points for related publications and subscriptions. Further, info-stations also assist in locating vehicles that have subscribed to information items. We consider different possible deployments of this hybrid VANET with respect to the number of info-stations and their physical connectivity with each other. We perform simulations to assess the performance of our approach in these different deployment scenarios and discuss their applicability in urban and semi-urban areas.