AP-STA Association Control for Throughput Maximization in Virtualized WiFi Networks

Multihoming has been broadly employed by large enterprises, and stub networks to augment the availability and reliability of their Internet access. In this technique, the edge network is connected to the Internet through multiple upstream Internet Service Providers (ISPs) rather than one. Thus far, different aspects of multihomed networks have received intensive attention in the research community. However, there have been quite a few works on the selection methodologies of upstream ISPs for a multihomed network which is definitely a primary prerequisite for other challenges in this area. In this paper, we try to address the ISP selection problem for provisioning of survivable end-to-end connections in multihomed networks. We first argue about different design decisions that the network operator has to make for support of resiliency against single-link network failures. Then, the minimum ISP selection problem is defined in which the goal is to pick the minimum number of upstream ISPs such that by multihoming to them, the major connections of the network would achieve a satisfactory level of resiliency against link failures. Then, we propose a brute-force method to optimally unravel this problem. Despite the NP-hardness of our problem, we show that the proposed method can be used in practice to solve the problem in tolerable manner.

Content delivery networks (CDNs) deliver Web content to end-users from a large distributed platform of Web servers hosted in data centers belonging to thousands of Internet service providers (ISPs) around the world. The bandwidth cost incurred by a CDN is the sum of the amounts it pays each ISP for routing traffic from its servers located in that ISP out to end-users. A large enterprise may also contract with multiple ISPs to provide redundant Internet access for its origin infrastructure using technologies such as multihoming and mirroring, thereby incurring a significant bandwidth cost across multiple ISPs. This paper initiates the formal study of bandwidth cost minimization in the context of a large enterprise or a CDN, a problem area that is both algorithmically rich and practically very important. First, we model different types of contracts that are used in practice by ISPs to charge for bandwidth usage, including average, maximum, and 95th-percentile contracts. Then, we devise an optimal offline algorithm that routes traffic to achieve the minimum bandwidth cost, when the network contracts charge either on a maximum or on an average basis. Next, we devise a deterministic (resp., randomized) online algorithm that achieves cost that is within a factor of 2 (resp., e/(e - 1)) of the optimal offline cost for maximum and average contracts. In addition, we prove that our online algorithms achieve the best possible competitive ratios in both the deterministic and the randomized cases. An interesting theoretical contribution of this work is that we show intriguing connections between the online bandwidth optimization problem and the seemingly-unrelated but well-studied ski rental problem where similar optimal competitive ratios are known to hold. Finally, we consider extensions for contracts with a committed amount of spend (CIRs) and contracts that charge on a 95th-percentile basis

The International Telecommunication Union (ITU-T) is developing an architecture for Next Generation Network (NGN) to provide end-to-end Quality of Service (e2e QoS), for which Internet service provider (ISP) interconnections play a key role. Furthermore, for an effective e2e QoS-guaranteed interconnection across multiple ISPs, it is of a great help to develop a framework which enables ISPs to trade their unused network capacity. This study presents Hub-and-Spoke (H&S) interconnection model, where the hub called Neutral Internet Business eXchange (NIBX) arranges Bandwidth Trading (BT) on the basis of the market mechanism. After introducing qualitative and quantitative justifications of the H&S NIBX interconnection model, we propose a platform prototype for BT based upon the H&S NIBX architecture. Presented also are some detailed descriptions of key functional elements together with decision models embedded in the functions. Operations scenarios show potential benefits of the NIBX + BT architecture for ensuring e2e QoS, the ultimate goal of ITU-T’s NGN.

Network Slicing (NS) technique is comprehensively reshaping the next-generation communication networks (e.g. 5G, 6G). Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) predominantly control the flow of service functions on NS to incorporate versatile applications as per user demands. In the virtualized-Software Defined Networking vSDN environment, a chain of well-defined virtual network functions (VNFs) are installed on Service Function Chains (SFCs) by multiple Internet Service Providers (ISPs) concurrently. Generation, allocation, re-allocation, release and destroying associative VNFs on SFC is an extremely difficult task while keeping high selection accuracy. Towards solving this fundamental issue, in this work, we have proposed a multi-layered SFC formation for adaptive VNF allocation on dynamic slices. We have formulated an ILP to address the VNF-EAP (VNF-Embedding and Allocation Problem) over real network topology (AT&T Topology). Leveraging machine learning techniques we have shown an intelligent VNF selection mechanism to optimize resource utilization. The performance evaluation shows remarkable efficiency on ML-driven dynamic VNF selections over static allocations on SFCs by halving resource usage. Further, we have also studied a VNF typecasting technique for service backup on outage slices in the field of disaster management activities.

ICT 기술의 발전으로 인해 IPTV, 인터넷 전화 등 다양한 서비스가 인터넷 기반으로 제공되고, 이러한 서비스가 다수의 사업자 망을 통해 전달되고 있다. 본 연구는 이러한 네트워크 환경에서 서비스의 품질에 가장 많은 영향을 미치고 이용자의 주관적 품질 판단에 결정적인 역할을 하는 종단간 인터넷 서비스 품질 평가에 관해 국제 표준을 기반으로 국내 실정에 적합한 평가 방안을 제시한다. 이 결과, 시간지연, 지연변이, 패킷 손실률이 품질 평가 지표로 선정되었으며 인터넷 서비스 제공자들 간에 정보 공유를 최소화하면서 이를 예측할 수 있는 방안을 전통적인 통계방법을 사용하여 제시한다.

An internet service provider (ISP) tries to maximize profit by choosing an appropriate price for an offered service. In this paper, a system of two identical ISPs is considered. When ISPs independently choose a price to charge to maximize profit and each ISP repeatedly tries to improve profit by changing the price till no further improvements are possible, they may reach an equilibrium called the Nash equilibrium. Another strategy is that one ISP announces an appropriate price in advance and the other ISP chooses the best response strategy. This leads to Stackelberg competition. Both these strategies are compared in the paper. In this paper, it is assumed that few clients have access to multiple ISPs by using multi-SIM handheld devices such as smartphones and tablets. The clients who have access to multiple-ISPs choose an appropriate ISP for service based on the price of the service. The clients who have access to only one ISP, have no choice but to take service from the ISP. Simulations show that the ISP who announces an appropriate price in advance is likely to do better as compared to the ISP who decides the price later after observing the price of the announcer. Simulations also show that announcing an appropriate price in advance is better instead of independently deciding the price which may lead to a Nash equilibrium in terms of profit of the ISPs and quality of service provided to the clients.

We model how Internet Service Providers design tier rates, tier prices, and network capacity. Web browsing and video streaming are considered as the two dominant Internet applications. We propose a novel set of utility functions that depend on a user's willingness to pay for each application, the performance of each application, and the time devoted to each application. For a monopoly provider, the demand function for each tier is derived as a function of tier price and performance. We first give conditions for the tier rates, tier prices, and network capacity that maximize Internet Service Provider profit, defined as subscription revenue minus capacity cost. We then show how an Internet Service Provider may simplify tier and capacity design, by allowing their engineering department to set network capacity, their marketing department to set tier prices, and both to jointly set tier rates. Numerical results are presented to illustrate the magnitude of the decrease in profit resulting from such a simplified design.

With the popularity of smart devices such as smartphones, tablets, contents that traditionally be viewed on a personal computer, can also be viewed on these smart devices. The demand for contents thus is increasing year by year, which makes the content providers (CPs) get high revenue from either users' subscription or advertisement. On the other hand, Internet service providers (ISPs), who keep investing in the network technology or capacity to support the huge traffic generated by contents, do not benefit directly from the content traffic. One choice for ISPs is to charge CPs to share the revenue from the huge content traffic. Then ISPs will have enough incentives to invest in network infrastructure to improve quality of services (QoS), which eventually benefit CPs and users. This paper presents a novel economic model called Stackelberg-Bertrand game to capture the interaction and competitions among ISPs, CPs and users when ISPs charge CPs. A generic user demand function is assumed to capture the sensitivity of demand to prices of ISPs and CPs. The numerical results show that the price elasticity of ISP and CP plays an important part on the payoff of the ISP and CP.

Load balancing is a technique to distribute traffic load into two or more lanes to reach balanced connection, optimized traffic performance, maximized data throughput, minimized delay, and avoiding data overload. Load balancing in a computer network used to modulate the balance of bandwidth usage between multiple internet service provider. This research contains Load Balancing performance test on HTTP, FTP, and VoIP. Testing application used is OPNET Modeler 14.5 simulator, and load balancing algorithm which being tested is Least Connection, Round Robin, and Ratio. The test results shows generally Ratio is better than Least Connection and Round Robin. Ratio excels on handling End-to-End Delay and Jitter in VoIP, while Least Conncetion shows the highest throughput value in all test cases.

In this research work we investigate an innovative economical and technological IPv4/IPv6 a novel multi homing migrational model named ‘Multicost6’. The ‘Multicost6’ offers innovative economical and technological charges like the first one is the real amount of hardware which indicates an economical value and second one is real rate of software like training cost and the third one is labour outlay and fourth one is an un anticipated charge and fifth one is named such as another cost required for multi homing transition. The availability of two or more connectivity providers (configuration known as multi homing) allows improvements in failure tolerance and enables traffic engineering capabilities. Multi homing allows a site/node to connect to multiple Internet service providers (ISPs) simultaneously. The proposed solution consists of multiple mechanisms that provide different benefits to the multi homed site. In this approach,each multi homed host is assigned multiple prefixes from its upstream providers,and it creates the interface identifier part of its addresses. With the advantages of the eased renumbering network mechanism and the large addressing space introduced by IPv6 network,multi homing will become much more popular. In this innovative research work we have propounded a technical and an economical expenditure estimation model(Multicost6) for Hardware,Software,Labour,Un anticipated and Other costs for University of Mysore(DoS in CS,Manasagangotri,Mysore-6) and Mangalore University(Department of CS,Mangalagangotri,Mangalore) in INDIA. The experiment was organized for various sizes of LAN’s with different size digital computers such as Desktop machines,Laptops,Main frame computers,Mini computers,Super computer etc to study and analyze the effect of charge estimation model(Multicost6) for multi homing technique and the results proves that multicost6 expense estimation model for multi homing host is Low,Medium and High based on Hardware,Software,Labour and Other expenditure estimation factors. In order to Plot Bar chart,Pie chart we used Matlab 7.11.0(R2010b) and to compute Simulation results we have also adopted NS2.

In this paper, we present some interesting issues of resource allocation in network virtualization. We also propose RAiNV, a resource allocation framework to handle those issues. Sharing of resources is in the heart of network virtualization. The key idea of network virtualization is to replace conventional Internet service provider (ISP) with two separate business entities: infrastructure providers (InP) and service providers (SP). The InPs are the owners of resources. They are responsible for maintaining a certain level of quality of service (QoS) at the physical layer. The SPs lease resources from InPs. They offer various services to end users. It is more realistic to think about a scenario with multiple InPs and multiple SPs. A single service provider (SP) can integrate resources from multiple InPs. Similarly, a single InP can distribute resources to multiple SPs. As a result, optimal resource sharing becomes a challenging task. Resource allocation covers all the virtual network (VN) provisioning matters. Major parts include resource advertisement, request, negotiation, etc. The RAiNV aims to ease dealing with multiple InPs. Its performance is evaluated using obtained numerical results through simulations.

In this work, we introduce a new Markov model for the distributed coordination function (DCF) protocol which accurately predicts the network throughput of 802.11 networks under realistic traffic load. Specifically, we provide an improved treatment of the post backoff, the probability of immediate transmission after DIFS, and the probability of having a new packet for transmission after the post backoff. A key feature of our model is the ability to predict the optimal network throughput and the network capacity (in terms of number of stations with acceptable QoS). Knowledge of the network capacity aids to network planning and QoS for multimedia applications. Another feature is that the model converges to a saturated model when the number of stations becomes large. Based on this feature, we introduce a new method to estimate the lower bound of network capacity.

Improving throughput in SWIPT-based wireless multirelay networks with relay selection and rateless codes

The mammoth Internet traffic growth puts a significant load on Internet Service Provider's (ISP) network capacity which impacts a wide range of network Quality of Service (QoS) metrics such as latency, jitter, throughput, packet loss, link utilization, load balancing, and service availability. From the ISP's perspective, understanding the possible impact of the future Internet traffic on its network QoS is critical for provisioning their network capacity in a cost-effective manner while meeting Service Level Agreement (SLA) between an operator and its customers. To achieve the above goal, one needs a mechanism that is capable of taking input from the projected future traffic, assign the forecasted traffic over the end-to-end network, and then analyses the impact on the network's QoS status. In this paper, we developed a novel network planning framework, namely Network Impact Modeling and Analysis (NIMA) that uses novel methods and techniques to alert ISP's network capacity planners on the: (a) links that are subject to high-risk in terms of congestion; (b) impact on latency, jitter, packet loss, and throughput; (c) impact on load balancing; and finally suggests an optimal routing strategy that can improve the overall network health. For simulation purposes, we used Mininet in combination with a floodlight controller for implementation. The experiments are performed on different sized mesh topologies to test the effectiveness of our proposed framework.

Zero Rating, Content Quality and Network Capacity