اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدScalable peer-to-peer streaming for live entertainment content
156
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We present a system for streaming live entertainment content over the Internet originating from a single source to a scalable number of consumers without resorting to centralised or provider- provisioned resources. The system creates a peer-to-peer overlay network, which attempts to optimise use of existing capacity to ensure quality of service, delivering low start-up delay and lag in playout of the live content. There are three main aspects of our solution. Firstly, a swarming mechanism that constructs an overlay topology for minimising propagation delays from the source to end consumers. Secondly, a distributed overlay anycast system that uses a location-based search algorithm for peers to quickly find the closest peers in a given stream. Finally, a novel incentives mechanism that encourages peers to donate capacity even when the user is not actively consuming content.
قيم البحث
اقرأ أيضاً
Scalability and efficient global search in unstructured peer-to-peer overlays have been extensively studied in the literature. The global search comes at the expense of local interactions between peers. Most of the unstructured peer-to-peer overlays
do not provide any performance guarantee. In this work we propose a novel Quality of Service enabled lookup for unstructured peer-to-peer overlays that will allow the users query to traverse only those overlay links which satisfy the given constraints. Additionally, it also improves the scalability by judiciously using the overlay resources. Our approach selectively forwards the queries using QoS metrics like latency, bandwidth, and overlay link status so as to ensure improved performance in a scenario where the degree of peer joins and leaves are high. User is given only those results which can be downloaded with the given constraints. Also, the protocol aims at minimizing the message overhead over the overlay network.
Peer-to-peer (p2p) content delivery is promising to provide benefits like cost-saving and scalable peak-demand handling in comparison with conventional content delivery networks (CDNs) and complement the decentralized storage networks such as Filecoi
n. However, reliable p2p delivery requires proper enforcement of delivery fairness, i.e., the deliverers should be rewarded according to their in-time delivery. Unfortunately, most existing studies on delivery fairness are based on non-cooperative game-theoretic assumptions that are arguably unrealistic in the ad-hoc p2p setting. We for the first time put forth the expressive yet still minimalist securities for p2p content delivery, and give two efficient solutions FairDownload and FairStream via the blockchain for p2p downloading and p2p streaming scenarios, respectively. Our designs not only guarantee delivery fairness to ensure deliverers be paid (nearly) proportional to his in-time delivery, but also ensure the content consumers and content providers to be fairly treated. The fairness of each party can be guaranteed when the other two parties collude to arbitrarily misbehave. Moreover, the systems are efficient in the sense of attaining asymptotically optimal on-chain costs and optimal deliverer communication. We implement the protocols to build the prototype systems atop the Ethereum Ropsten network. Extensive experiments done in LAN and WAN settings showcase their high practicality.
To mitigate the attacks by malicious peers and to motivate the peers to share the resources in peer-to-peer networks, several reputation systems have been proposed in the past. In most of them, the peers evaluate other peers based on their past inter
actions and then aggregate this information in the whole network. However such an aggregation process requires approximations in order to converge at some global consensus. It may not be the true reflection of past behavior of the peers. Moreover such type of aggregation gives only the relative ranking of peers without any absolute evaluation of their past. This is more significant when all the peers responding to a query, are malicious. In such a situation, we can only know that who is better among them without knowing their rank in the whole network. In this paper, we are proposing a new algorithm which accounts for the past behavior of the peers and will estimate the absolute value of the trust of peers. Consequently, we can suitably identify them as a good peers or malicious peers. Our algorithm converges at some global consensus much faster by choosing suitable parameters. Because of its absolute nature it will equally load all the peers in network. It will also reduce the inauthentic download in the network which was not possible in existing algorithms.
This paper proposes an analytical framework for peer-to-peer (P2P) networks and introduces schemes for building P2P networks to approach the minimum weighted average download time (WADT). In the considered P2P framework, the server, which has the inf
ormation of all the download bandwidths and upload bandwidths of the peers, minimizes the weighted average download time by determining the optimal transmission rate from the server to the peers and from the peers to the other peers. This paper first defines the static P2P network, the hierarchical P2P network and the strictly hierarchical P2P network. Any static P2P network can be decomposed into an equivalent network of sub-peers that is strictly hierarchical. This paper shows that convex optimization can minimize the WADT for P2P networks by equivalently minimizing the WADT for strictly hierarchical networks of sub-peers. This paper then gives an upper bound for minimizing WADT by constructing a hierarchical P2P network, and lower bound by weakening the constraints of the convex problem. Both the upper bound and the lower bound are very tight. This paper also provides several suboptimal solutions for minimizing the WADT for strictly hierarchical networks, in which peer selection algorithms and chunk selection algorithm can be locally designed.
Open and anonymous nature of peer to peer networks provides an opportunity to malicious peers to behave unpredictably in the network. This leads the lack of trust among the peers. To control the behavior of peers in the network, reputation system can
be used. In a reputation system, aggregation of trust is a primary issue. Algorithm for aggregation of trust should be designed such that, it can converge to a certain finite value. Absolute Trust is one of the algorithm, which is used for the aggregation of trust in peer to peer networks. In this letter, we present the generalized analysis of convergence of the Absolute Trust algorithm.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
