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Introduction Opportunistic Content Caching Vehicular Mobility Role in Cooperative Content Caching Conclusions and Future Work Opportunistic and Cooperative Content Caching Paradigms in Wireless Networks Osama Gamal Mohamed Attia Wireless Intelligent Networks Center School of Communication and Information Technology Nile University, Egypt August 5, 20121 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Opportunistic Content Caching Vehicular Mobility Role in Cooperative Content Caching Conclusions and Future Work Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work2 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work3 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Content Caching Content caching has been introduced in the Internet, and later for wireless extensions, to enhance user experience (retrieval time) and reduce network load. It allows nodes to store a copy of the data it do request in a previous time slot for a future use. Different caching paradigms emerged in MANETs: Non-cooperative: nodes make independent decisions to cache data or paths. Cooperative: exploits the wisdom of the crowd and creates diversity. Opportunistic: utilizes the data sent in the network for future requests.4 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work5 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Main Contribution In the ﬁrst part: 1 We introduce the novel concept of OCC whereby nodes cache overheard content delivered by the content server (CS) to nearby nodes. 2 We cast the OCC problem into a mathematical framework inspired by the diversity-multiplexing tradeoff ﬁrst introduced by David Tse. 3 We characterize the diversity gain of OCC and quantify the improvement over a baseline which does not leverage the inherent broadcast nature of wireless transmissions6 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Main Contribution Continue .. In the second part: 1 Introduce a deﬁnition for the Probability of Outage in the context of cooperative content caching. 2 Characterize, analytically, the outage probability under vehicular and random mobility scenarios. 3 Compare, using simulations, the outage performance under sample mobility regimes.7 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work8 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Background Opportunistic Content Caching Main Contribution Vehicular Mobility Role in Cooperative Content Caching Related Work Conclusions and Future Work Related Work Content caching concept has been ﬁrst introduced to the Internet, especially for web [Wang ’99, Barish et al. ’00]. Cooperative Content Caching in MANETs: Yin et al., 2006: proposed three schemes for cooperative caching in ad hoc networks with the objective of reducing the query delay. Fiore et al., 2009: introduced a new metric (presence index) deciding for how long should a data chunk be cached. El Gamal et al. 2010: introduced novel proactive resource allocation scheme and analyzed it under DMT framework. Fiore et al., 2007: studied the impact of highway and urban mobility on VANET routing protocols.9 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work10 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Assumptions Time slotted system of a single content server (CS) and multiple nodes. For any node i, let N average number of nodes randomly dispersed within the CS radio range. i A ﬁle is composed of m ﬁxed number of chunks. Chunk requests arrive at an arbitrary node i in each slot according to a Poisson process with rate λi = λ. Requests arrive at the beginning of a slot and each chunk is retrieved in one slot using one resource (channel). Node i has wireless capacity with total number of channels C. Delivering requested content to node i Node’s cache size is M chunks, M >> C (supported Cache overheard content delivered to node i for T slots by Moore’s law).11 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Opportunistic Content Caching Scheme Start All nodes run in promiscuous passive mode. Overhear transmitted data chunks between the Node i overhears and stores or Content Server (CS) and nearby nodes updates the new content sent from the Content Server to any of the nearby nodes. No Encounter a new Node i caches new, or updated, data chunk? overheard data chunks for T time Yes slots. Does it exist in No Given the overlap in interests, p, a current cache? Cache for T time slots query issued by node i may be Yes served from its own cache or from Update if newer the content server (0 ≤ p ≤ 1).12 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work13 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Diversity-Multiplexing Tradeoff Mathematical Framework Originally proposed by David Tse et al. for multi-antenna wireless communication. DMT allows analyzing the asymptotic decay rate of outage probability with the system capacity C. We assume that the total request arrival rate per slot λ scales with capacity in two different regimes: Linear Scaling: λ = γC Polynomial Scaling: λ = Cγ where γ serves as the bandwidth utilization factor, 0 ≤ γ ≤ 1 As γ goes to 1, the system becomes critically stable and more subject to outage events.14 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Deﬁnition of Outage Deﬁnition We deﬁne the probability of outage at any arbitrary node as the probability of not being able to serve a request within a time slot. In this case, Opportunistic Caching, an outage event takes place when a node is not being able to retrieve a requested data chunk, in a given time slot, from the content server, or the cached data overheard from chunk retrievals of nearby nodes.15 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Diversity Gain Overhearing and caching data chunks retrieved by nearby nodes from the Content Server yields multi-user diversity. Overlapping requests may be resolved locally using the overheard data cached from prior deliveries to the N nearby nodes, at no cost versus download from the content server at a delay and delivery cost. We deﬁne diversity gain under as follows: 1 Linear Scaling: log P(O) d(γ) = lim − C→∞ C 2 Polynomial Scaling: log P(O) d(γ) = lim − C→∞ C log C16 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work17 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Retrieval from Content Server Only (Baseline) All the requests will be served by the content server with no provisions for caching or cooperation among the nodes. The probability of outage, P(O) , will be only the outage at server: P(O) = Pcs (O) Let Q(n) be the number of requests at a node in the time slot n. We can express the probability of outage as follows: P(O) = P(Q(n) > C) ∞ e−λ λk = k! k=C+118 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Diversity Gain of Baseline Retrieval From the previous equations, we can rewrite the diversity gain in case of linear capacity scaling as follows: 1 dbl (γ) = − lim log P(Q(n) > C) c→∞ C Based on the analysis by El Gamal et al., it can be shown that the diversity gain of the baseline no caching system, in case of linear capacity scaling, is given by, dbl (γ) = γ − 1 − log γ Also, in case of polynomial capacity scaling we can write the diversity gain as: 1 dbl (γ) = − lim log P(Q(n) > C) c→∞ C log C =1−γ19 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work20 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Opportunistic Content Caching (OCC) In this paradigm, each node has a cache storage that hosts data overheard from nearby nodes within the past T time slots. The outage probability is the probability of not ﬁnding the requested chunk in the cached overheard data and not being able to retrieve it from the Content Server due to the limited wireless capacity, C, that is, P(O) = Pcs (O)Poh (O)N Poh (O) is the probability of not being able to resolve the query from the cached overheard data. The outage probability Poh (O) equals to the probability that a node of the N nearby nodes didn’t make any overlapping requests within the last T time slots.21 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Opportunistic Content Caching (OCC) Continue .. Poh (O) can be written as follows Poh (O) =[P(O|Q(n) ≤ C)P(Q(n) ≤ C) + P(O|Q(n) > C)P(Q(n) > C)]T We know that, the outage probability given the number of requests is less than or equal C equals to e−pλ which is the probability of not ﬁnding overlapping requests. Also, the probability of outage given the number of requests greater than C is guaranteed to be equal to 1. Hence, T Poh (O) = e−pλ P(Q(n) ≤ C) + P(Q(n) > C) T = e−pλ + (1 − e−pλ )P(Q(n) > C)22 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Diversity Gain of Opportunistic Content Caching Continue .. By substituting in the outage deﬁnition and taking the logarithm: log P(O) =TN log e−pλ + (1 − e−pλ )P(Q(n) > C) + log P(Q(n) > C) Simplifying and solving for the linear scaling, we ﬁnd that, dopp (γ) = TN min(pγ, dbl (γ)) + dbl (γ) So, if there is no overlapping requests between nodes (i.e. p = 0), we ﬁnd out that dopp (γ) = dbl (γ). However, at the total overlap between nodes’ requests (i.e. p = 1), it is clear that dopp (γ) = (TN + 1)dbl (γ). Also, solving for the polynomial scaling case show that no improvement over baseline-retrieval: dopp (γ) = dbl (γ) = 1 − γ23 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work24 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Results and Insights We show the result of the probability of outage under the linear and polynomial capacity scaling cases. WLOG, We plotted the curves at an arbitrary values listed in the table below in order to show the improvement of the opportunistic content caching over the baseline scenario. Parameter Value Multiplexing gain (γ) 0.75 Interest overlap probability (p) 0.6 Number of neighbor (N) 3 nodes Caching time (T) 6 slots25 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Outage probability performance 0 0 10 10 −10 10 −10 10 Outage Probability P(O) Outage Probability P(O) −20 10 −20 10 −30 10 −30 10 −40 10 Baseline Baseline Opportunistic Opportunistic −40 −50 10 10 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Capacity (C) Capacity (C log C) (a) Linear Scaling Case (b) Polynomial Scaling Case26 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights Diversity-Multiplexing Tradeoff 5 1 Baseline Baseline 4.5 Opportunistic 0.9 Opportunistic 4 0.8 3.5 0.7 3 0.6 Diversity Diversity 2.5 0.5 2 0.4 1.5 0.3 1 0.2 0.5 0.1 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Multiplexing Gain (γ) Multiplexing Gain (γ) (c) Linear Scaling Case (d) Polynomial Scaling Case No improvement in terms of diversity gain for the polynomial scaling case. This could be justiﬁed since the content caching scheme under polynomial scaling with γ an overlapping factor that grows as e−pC is very slow.27 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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System Model Introduction DMT Framework for Opportunistic Content Caching Opportunistic Content Caching Baseline Retrieval Vehicular Mobility Role in Cooperative Content Caching Opportunistic Caching Conclusions and Future Work Results and Insights The effect of interest overlap probability 0 0 10 10 −10 −5 10 10 Outage Probability P(O) Outage Probability P(O) −20 10 −10 10 −30 10 −15 10 −40 10 Baseline Baseline Opportunistic (p = 0.1) Opportunistic (p = 0.1) −20 10 Opportunistic (p = 0.4) −50 Opportunistic (p = 0.4) 10 Opportunistic (p = 0.7) Opportunistic (p = 0.7) Opportunistic (p = 1) Opportunistic (p = 1) −25 −60 10 10 0 2 4 6 8 10 12 14 16 18 20 0 10 20 30 40 50 60 Capacity (C) Capacity (C log C) (e) Linear Scaling Case (f) Polynomial Scaling Case28 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work29 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Motivation Vehicular Ad hoc Networks (VANET) is a promising emerging networking paradigm. VANETs are envisioned to improve the driving experience and save lives on the roads. Cooperative content caching (CCC) is a plausible technology for content delivery in VANETs. Content delivery to mobile platforms, e.g., vehicles, from infrastructure is resource- and time-consuming. Hence, cooperation presents an opportunity. Is there a performance gain for the vehicular mobility over random mobility. If there is a performance gain, how to quantify it?30 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work31 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results System Model We assume toy model of two nodes (adequate to capture the problem). Users are interested in items where each information Y item consists of multiple chunks. Direction of Nodes starts with empty caches. Movement Chunk requests arrive at node i according to a l r x Poisson process with rate λ. xx θ X Fixed transmission power which translates to a n1 n2 circular range of radius r. If the requesting node gets a query resolved, it caches a copy of the chunk for an arbitrarily long time.32 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Mobility Models Random Mobility: x: Distance between the two Y vehicles, x ∼ Uni[−r, r]. v: Relative velocity, Direction of Movement v ∼ Uni[vmin , vmax ]. θ: Direction of movement, θ ∼ Uni[θmin , θmax ]. Vehicular Mobility: l r x x ∼ Uni[−r, r]. v ∼ Uni[vmin , vmax ]. xx θ X Direction of movement is deterministic, θ = π/2 for a n1 n2 straight freeway segment.33 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work34 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Probability of Outage Deﬁnition We deﬁne the probability of outage, Pn1 , as the probability of not ﬁnding a data o chunk at a single-hop neighbor within time period (t, t + τ ). Pn1 can be deﬁned as the complement of the probability of node n1 ﬁnding a o chunk, denoted Pn1 . f The event of ﬁnding a data chunk happens when 3 independent events jointly take place: n2 requests at least a chunk within the period τ . There is an interest overlap with probability γ. The two nodes are within the communication range (Pneigh ). Pn1 = 1 − Pn1 o f = 1 − γ(1 − e−λτ )Pneigh35 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Quantifying Pneigh in Random Mobility n2 will stay within the radio range of n1 after time τ iff if vτ is less than or equal to distance l. l= 1 − x2 sin2 θ − x cos θ Hence, Pneigh = P(vτ ≤ l) = P(vτ ≤ 1 − x2 sin2 θ − x cos θ) = f (x, u, θ)dx du dθ x,u,θ∈Dr The integration is solved numerically due to its complexity.36 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Quantifying Pneigh in Vehicular Mobility In this case θ = π/2, and, √ l = 1 − x2 . Hence, Pneigh = P(τ vmin ≤ u ≤ min(τ vmax , l)) = f (x, u)dxdu x,u∈Dv umax √ 1 − u2 = du umin umax − umin Dv is the region over which x and u satisfy the inequality: τ vmin ≤ u ≤ min(τ vmax , 1 − x2 )37 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Outline 1 Introduction Background Main Contribution Related Work 2 Opportunistic Content Caching System Model DMT Framework for Opportunistic Content Caching Baseline Retrieval Opportunistic Caching Results and Insights 3 Vehicular Mobility Role in Cooperative Content Caching Motivation System Model Outage Performance Analysis Performance Results 4 Conclusions and Future Work38 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Simulation Settings We develop Matlab simulations to verify the analytical results. Analytical and simulation results are generated using the following system parameters: Parameter Value Overlap ratio (γ) 0.7 Requests arrival rate (λ) 3 requests/sec Radio range (r) 150 m Minimum relative speed (vmin ) 5 km/hr Maximum relative speed (vmax ) 50 km/hr39 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Performance Results 1 1 Random Mobilty (Analysis) 0.9 Vehicular Mobility (Analysis) 0.9 ) Random Mobility (Simulation) neigh 0.8 Vehicular Mobility (Simulation) Probability of being in reach (P 0.8 0.7 Probability of Outage 0.6 0.7 0.5 0.6 0.4 0.3 0.5 Random Mobilty (Analysis) Vehicular Mobility (Analysis) 0.2 0.4 Random Mobility (Simulation) 0.1 Vehicular Mobility (Simulation) 0.3 0 0 20 40 60 80 100 120 0 20 40 60 80 100 120 τ (sec) τ (sec) (g) Probability of being in reach (h) Outage Probability For the range of Po of practical interest, vehicular mobility has lower probability of outage than random mobility.40 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Motivation Opportunistic Content Caching System Model Vehicular Mobility Role in Cooperative Content Caching Outage Performance Analysis Conclusions and Future Work Performance Results Performance Results Continue.. Comparing random mobility to road width-limited vehicular mobility (5-lane freeway with 4 meters lane width). 1 0.9 0.8 Probability of Outage 0.7 0.6 0.5 0.4 Random Mobility Vehicular Mobility 0.3 0 20 40 60 80 100 120 τ (sec) Conﬁrms the superiority of vehicular mobility especially in the practical range of interest.41 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Conclusions In the ﬁrst part: Then, w Follows, We proposed a new paradigm for content caching that involves exploiting the prior resolved queries of the neighbor users for future requests. We formally set forth the deﬁnition of outage event in lights of a plausible system model. We conducted diversity-multiplexing tradeoff analysis (diversity as chances of resolving queries in terms of number of nodes and time slots). We evaluated, mathematically, the outage probability and diversity gains of the system under different settings. Finally, numerical results that validate our claims are shown and insights are drawn.42 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Conclusions Continue .. In the second part: We introduced a formal deﬁnition for the probability of outage in the context of cooperative content caching. Then, we characterized, analytically, the outage probability under vehicular and random mobility. We veriﬁed the analytical results using simulation studies which exhibit complete agreement. Results conﬁrm the opportunity created by the structured vehicular mobility which would inspire future cooperative caching schemes. The numerical results demonstrate up to 32% improvement in the outage performance (and 16% on the average) for the studied plausible scenarios where the probability of outage is below 0.5.43 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Future Work Our work in the ﬁrst part could be oriented as follows: Implement a distributed algorithm that makes use of the main characteristics of OCC paradigm. Analyzing on the effect of mobility patterns on the opportunistic caching paradigm. Extend the opportunistic content caching scheme considering the privacy and anonymity issues. Develop a distributed and cooperative algorithm to calculate the optimum caching time for a speciﬁc data chunk in order to utilize the node’s storage.44 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Future Work Continue .. The second part of this work can be extended along the following research directions: Generalize the model to relax few assumptions of practical relevance (N, γ, Tc ). Model and quantify the diversity gains attributed to nodes’ cooperation. Quantify the outage performance for other vehicular mobility models. Quantify the cooperation diversity gain that is above and beyond the mobility gains explored here. Develop novel cooperative caching schemes that capture the structured nature of vehicular mobility.45 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Publications Osama Attia, Tamer ElBatt, "On the Role of Vehicular Mobility in Cooperative Content Caching", accepted in IEEE WCNC 2012, Vehicular Workshop, April, 2012. Osama Attia, Tamer ElBatt, "Opportunistic Content Caching in Wireless Networks", under submission.46 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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Introduction Conclusions Opportunistic Content Caching Future Work Vehicular Mobility Role in Cooperative Content Caching Publications Conclusions and Future Work Thank You! Any Questions?47 / 47 Osama Gamal M. Attia Content Caching Paradigms in Wireless Networks
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