The basic idea is to let each caching node be only responsible for refreshing a specific set of caching nodes, so as to maintain cache freshness in a distributed and hierarchical manner.
Abstract:
Opportunistic mobile networks consist of personal mobile devices which are intermittently connected with each other. Data access can be provided to these devices via cooperative caching without support from the cellular network infrastructure, but only limited research has been done on maintaining the freshness of cached data which may be refreshed periodically and is subject to expiration. In this paper, we propose a scheme to efficiently maintain cache freshness. Our basic idea is to let each caching node be only responsible for refreshing a specific set of caching nodes, so as to maintain cache freshness in a distributed and hierarchical manner. Probabilistic replication methods are also proposed to analytically ensure that the freshness requirements of cached data are satisfied. Extensive trace driven simulations show that our scheme significantly improves cache freshness, and hence ensures the validity of data access provided to mobile users.
TL;DR: The current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients is described and AoI timeliness metrics are described.
TL;DR: In this paper, the authors summarize recent contributions in the broad area of AoI and present general AoI evaluation analysis that are applicable to a wide variety of sources and systems, starting from elementary single-server queues, and applying these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks.
TL;DR: A survey of the state-of-the-art research on SAN with focus on three aspects: routing and forwarding, incentive mechanisms, and data dissemination is presented.
TL;DR: This paper proposes an incentive-driven and freshness-aware pub/sub Content Dissemination scheme, called ConDis, for selfish OppNets, and shows that ConDis is superior to other existing schemes in terms of total freshness value, total delivered contents, and total transmission cost.
TL;DR: This work proposes a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources.
TL;DR: The nationwide network of sheldon m ross introduction to probability models solutions is dedicated to offering you the ideal service and will help you with this kind of manual.
TL;DR: The evaluations show that MaxProp performs better than protocols that have access to an oracle that knows the schedule of meetings between peers, and performs well in a wide variety of DTN environments.
TL;DR: BUBBLE is designed and evaluated, a novel social-based forwarding algorithm that utilizes the aforementioned metrics to enhance delivery performance and empirically shows that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social- based forwarding SimBet algorithm.
TL;DR: BUBBLE is designed and evaluated, a novel social-based forwarding algorithm that utilizes the aforementioned metrics to enhance delivery performance and empirically shows that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social- based forwarding SimBet algorithm.
Q1. What are the contributions mentioned in the paper "Distributed maintenance of cache freshness in opportunistic mobile networks" ?
In this paper, the authors propose a scheme to efficiently maintain cache freshness. Extensive tracedriven simulations show that their scheme significantly improves cache freshness, and hence ensures the validity of data access provided to mobile users.
Q2. Why is data forwarded in a “carry-and-forward” manner?
Due to the intermittent network connectivity in opportunistic mobile networks, data is forwarded in a “carry-and-forward” manner.
Q3. What is the effect of intentional refreshing on the cache freshness of data?
Due to possible version inconsistency among different data copies cached in the DAT, opportunistic refreshing may have some side-effects on cache freshness.
Q4. How many times did the decay of the CCDF of the inter-refreshing time?
Their results show that up to a boundary on the order of several minutes, the decay of the CCDF is well approximated as exponential.
Q5. What is the effect of changing the value of p on the refreshing overhead?
since different values of 𝑝 do not affect the calculation of utilities of data updates, such increase of refreshing overhead is relatively smaller than that of decreasing Δ.Section IV-C shows that the refreshing patterns of web RSS data is temporally skewed, such that the majority of data updates are generated during specific time periods of a day.
Q6. How is the performance of the proposed scheme evaluated?
The performance of their proposed scheme on maintaining cache freshness is evaluated by extensive tracedriven simulations on realistic mobile traces.
Q7. What is the effect of reducing the refreshing delay?
From Figure 12 the authors observe that, when the value of Δ is small, the cache freshness is mainly constrained by the network contact capability, and the actual refreshing delay is much higher than the required Δ. Such inability to satisfy the cache freshness requirements leads to more replications of data updates as described in Section V-B, and makes caching nodes more prone to perform opportunistic refreshing.