The rapid growth of peer-to-peer (P2P) networks in the past few years has brought with it increases in transit cost to Internet Service Providers (ISPs), as peers exchange large amounts of traffic across ISP boundaries. This ISP oblivious behavior has resulted in misalignment of incentives between P2P networks--that seek to maximize user quality--and ISPs--that would seek to minimize costs. Can we design a P2P overlay that accounts for both ISP costs as well as quality of service, and attains a desired tradeoff between the two? We design a system, which we call MultiTrack, that consists of an overlay of multiple whose purpose is to align these goals. mTrackers split demand from users among different ISP domains while trying to minimize their individual costs (delay plus transit cost) in their ISP domain. We design the signals in this overlay of mTrackers in such a way that potentially competitive individual optimization goals are aligned across the mTrackers. The mTrackers are also capable of doing admission control in order to ensure that users who are from different ISP domains have a fair chance of being admitted into the system, while keeping costs in check. We prove analytically that our system is stable and achieves maximum utility with minimum cost. Our design decisions and control algorithms are validated by Matlab and ns-2 simulations.
Traffic management and load balancing have become important as P2P networks grow in size. There has been work on traffic management for streaming traffic @cite_7 @cite_21 @cite_6 . In particular, @cite_7 focuses on server-assisted streaming, while @cite_21 @cite_6 aim at fair resource allocation to peers using optimization-decomposition. Closest to our setting is work such as @cite_12 @cite_1 @cite_14 , that study the need to localize traffic within ISP domains. In @cite_12 , the focus is on allowing only local communications and optimizing the performance by careful peer selection, while @cite_1 develops an optimization framework to balance load across ISPs using cost information. A different approach is taken in @cite_14 , wherein peers are selected based on inputs on nearness provided by CDNs (if a CDN directs two peers to the same cache, they are probably near by). Pricing and market mechanisms for P2P systems are of significant interest, and work such as @cite_19 use ideas of currency exchange between peers that can be used to facilitate file transfers. The system we design uses prices between mTrackers that map to real-world costs of traffic exchange, but do not have currency exchanges between peers which still use BitTorrent style bilateral barter.
@cite_14 @cite_7 @cite_21 @cite_1 @cite_6 @cite_19 @cite_12
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Load balancing plays an important role in improving scalability and stability in Content Delivery Networks (CDNs) to meet the increasing demand on bandwidth. This paper proposed a modified algorithm that takes into account the equilibrium between load balancing and redirection proximity. We extended a fluid queue model which is adopted in the existing literatures to the overall CDN system. In the system, scheduler selects proper replica server for each redistributed request by exploiting load differences between them. Furthermore, through limiting the migration distance for each request, the total costs mainly associated with delay are also effectively optimized. The simulation result indicates that the proposed algorithm can efficiently reduce redirection cost compared to Control-Law Balancing (CLB) algorithm at the expense of a bit of performance sacrifice of queue balancing. Besides, we found that the proposed mechanism has more benefit on queue balancing than CLB algorithm as well, when selecting an appropriate distance threshold. We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems. In this framework, we investigate the tension between storage resources, communication cost, and load balancing performance. To this end, we propose a randomized load balancing scheme which simultaneously considers cache size limitation and proximity in the server redirection process. In contrast to the classical power of two choices setup, since the memory limitation and the proximity constraint cause correlation in the server selection process, we may not benefit from the power of two choices. However, we prove that in certain regimes of problem parameters, our scheme results in the maximum load of order @math (here @math is the network size). This is an exponential improvement compared to the scheme which assigns each request to the nearest available replica. Interestingly, the extra communication cost incurred by our proposed scheme, compared to the nearest replica strategy, is small. Furthermore, our extensive simulations show that the trade-off trend does not depend on the network topology and library popularity profile details. Vehicular communications are becoming an emerging technology for safety control, traffic control, urban monitoring, pollution control, and many other road safety and traffic efficiency applications. All these applications generate a lot of data which should be distributed among communication parties such as vehicles and users in an efficient manner. On the other hand, the generated data cause a significant load on a network infrastructure, which aims at providing uninterrupted services to the communication parties in an urban scenario. To make a balance of load on the network for such situations in the urban scenario, frequently accessed contents should be cached at specified locations either in the vehicles or at some other sites on the infrastructure providing connectivity to the vehicles. However, due to the high mobility and sparse distribution of the vehicles on the road, sometimes, it is not feasible to place the contents on the existing infrastructure, and useful information generated from the vehicles may not be sent to its final destination. To address this issue, in this paper, we propose a new peer-to-peer (P2P) cooperative caching scheme. To minimize the load on the infrastructure, traffic information among vehicles is shared in a P2P manner using a Markov chain model with three states. The replacement of existing data to accommodate newly arrived data is achieved in a probabilistic manner. The probability is calculated using the time to stay in a waiting state and the frequency of access of a particular data item in a given time interval. The performance of the proposed scheme is evaluated in comparison to those of existing schemes with respect to the metrics such as network congestion, query delay, and hit ratio. Analysis results show that the proposed scheme has reduced the congestion and query delay by 30 with an increase in the hit ratio by 20 . It is becoming increasingly common to construct network services using redundant resources geographically distributed across the Internet. Content Distribution Networks are a prime example. Such systems distribute client requests to an appropriate server based on a variety of factors---e.g., server load, network proximity, cache locality---in an effort to reduce response time and increase the system capacity under load. This paper explores the design space of strategies employed to redirect requests, and defines a class of new algorithms that carefully balance load, locality, and proximity. We use large-scale detailed simulations to evaluate the various strategies. These simulations clearly demonstrate the effectiveness of our new algorithms, which yield a 60--91 improvement in system capacity when compared with the best published CDN technology, yet user-perceived response latency remains low and the system scales well with the number of servers.