![]() ![]() We also attempt to give lower bounds on P2P storage systems introducing the BIG system, in which we consider information globally. For each policy, we give either Markov Chain Models to efficiently compute the Mean Time To Data Loss (which is closely re- lated to the probability to lose data) or approximations of this quantity under certain assumptions. a brief state-of-the-art of the technology used in P2P storage sys- tems, we compare three different placement policies: two of them local, in which the data is stored in logical peer neighborhoods, and on of them global in which fragments are parted at random among the different peers. The way they distribute it, known as placement policy, has a significant impact on their behavior and reliability. To deal with common P2P problems such as peer failures or churn, such systems encode the user data into redundant fragments and distribute them among peers. Peer-to-peer systems are foreseen as an efficient solution to achieve reliable data storage at low cost. These results demonstrate that the combination of on-chip and off- chip TMR contributes towards building more dependable distributed embedded real-time systems. The paper quantifies the reliability benefits of the proposed MPSoC architecture by means of reliability modeling. Off-chip TMR with three MPSoCs can be used in the development of ultra-dependable applications (e.g., X-by-wire), where the reliability requirements exceed the reliability that is achievable using a single MPSoC. On-chip TMR improves the reliability of a MPSoC, e.g., by tolerating a transient fault in one of three replicated IP cores. Through its inherent fault isolation and determinism, the proposed MPSoC provides the basis for fault tolerance using Triple Modular Redundancy (TMR). This paper introduces such an architecture, which supports the integration of multiple, heterogeneous IP cores that are interconnected by a time-triggered Network-on-a-Chip (NoC). In conjunction with the increasing rates of transient faults in logic and memory associated with the continuous reduction of feature sizes, this situation creates the need for. The ongoing technological advances in the semiconductor industry make Multi-Processor System-on-a-Chips (MPSoCs) more attractive, because uniprocessor solutions do not scale satisfactorily with increasing transistor counts. The suitability of AIDA-based bandwidth allocation. In this paper we present AIDA and contrast it with traditional communication scheduling techniques used in conjunction with time-critical applications in general, and distributed multimedia systems in particular. Such a bound could be lowered so as to satisfy any level of confidence in the timeliness and reliability of the system. Instead, it guarantees a lower bound on the probability of fulfilling such constraints. AIDA is a probabilistic protocol in the sense that it does not guarantee the fulfillment of hard time constraints. In particular, redundancy is used to tolerate failures, to increase the likelihood of meeting tight time-constraints, and to ration (based on task priorities) the limited bandwidth. In AIDA redundancy is used to tackle several crucial problems. Rabin's IDA - is a communication protocol that uses redundancy to achieve both timeliness and reliability. This is exacerbated for users connected far from storage data-centers.Īll measurements used in our analyses are publicly available in anonymized form at the SimpleWeb trace repository: ĪIDA - a novel elaboration on Michael O. Lastly, our results show possible performance bottlenecks caused by both the current system architecture and the storage protocol. Secondly, we characterize the workload users in different environments generate to the system, highlighting how this reflects on network traffic. ![]() Our contributions are threefold: Firstly, we are the first to study Dropbox, which we show to be the most widely-used cloud storage system, already accounting for a volume equivalent to around one third of the YouTube traffic at campus networks on some days. By means of passive measurements, we analyze data from four vantage points in Europe, collected during 42 consecutive days. This paper presents a characterization of Dropbox, the leading solution in personal cloud storage in our datasets. ![]() This understanding is essential for designing efficient cloud storage systems and predicting their impact on the network. Very little is known about the architecture and the performance of such systems, and the workload they have to face. With a rush of providers to enter the market and an increasing offer of cheap storage space, it is to be expected that cloud storage will soon generate a high amount of Internet traffic. Personal cloud storage services are gaining popularity. ![]()
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