Jinbei Zhang

Coded caching under arbitrary popularity distributions

Caching plays an important role in reducing the backbone traffic when serving high-volume multimedia content. Recently, a new class of coded caching schemes have received significant interest because they can exploit coded multi-cast opportunities to further reduce backbone traffic. Without considering file popularity, prior works have characterized the fundamental performance limits of coded caching through a deterministic worst-case analysis. However, when heterogeneous file popularity is taken into account, there remain open questions regarding the fundamental limits of coded caching performance. In this work, for an arbitrary popularity distribution, we first derive a new information-theoretical lower bound on the expected transmission rate of any coded caching schemes. We then show that a simple coded-caching scheme attains an expected transmission rate that is at most a constant factor away from the lower bound (except a small additive term). Unlike other existing studies, the constant factor that we derived is independent of the popularity distribution.

Asymptotic Analysis on Secrecy Capacity in Large-Scale Wireless Networks

Since wireless channel is vulnerable to eavesdroppers, the secrecy during message delivery is a major concern in many applications such as commercial, governmental, and military networks. This paper investigates information-theoretic secrecy in large-scale networks and studies how capacity is affected by the secrecy constraint where the locations and channel state information (CSI) of eavesdroppers are both unknown. We consider two scenarios: 1) noncolluding case where eavesdroppers can only decode messages individually; and 2) colluding case where eavesdroppers can collude to decode a message. For the noncolluding case, we show that the network secrecy capacity is not affected in order-sense by the presence of eavesdroppers. For the colluding case, the per-node secrecy capacity of Θ([1/(√n)]) can be achieved when the eavesdropper density ψe(n) is O(n-β), for any constant β > 0 and decreases monotonously as the density of eavesdroppers increases. The upper bounds on network secrecy capacity are derived for both cases and shown to be achievable by our scheme when ψe(n)=O(n-β) or ψe(n)=Ω(log[(α-2)/(α)]n), where α is the path-loss gain. We show that there is a clear tradeoff between the security constraints and the achievable capacity. Furthermore, we also investigate the impact of secrecy constraint on the capacity of dense network, the impact of active attacks and other traffic patterns, as well as mobility models in the context.

Coded caching for files with distinct file sizes

Coded caching can exploit new multicast opportunities even when multiple users request different pieces of content, and thus can significantly reduce the backhaul requirement for serving high-volume content. However, existing studies of coded caching have been limited to the scenarios where all files of interest are of a common size. This work studies the performance limits of coded caching when the file sizes are different. We derive a new lower bound and an achievable upper bound for the worst-case transmission rate under coded caching, and show that these two bounds differ by at most a Θ(log K) factor, where K is the number of users in the system. There are two key novelties in our analysis. First, our lower bound is derived by considering a new cut-set bound where larger files are requested more times. The analysis of this new cut-set bound requires careful concatenation of several entropy inequalities. Compared to a lower bound using standard cut-set arguments, our lower bound is improved by a Θ(log K) factor. Second, our achievable scheme uses a caching probability that increases proportionally with the file size. Compared to schemes that use a common caching probability, the achievable rate of our scheme is reduced by a Θ K/logk2 factor.

Optimal Multicast Capacity and DelayTradeoffs in MANETs

In this paper, we give a global perspective of multicast capacity and delay analysis in Mobile Ad Hoc Networks (MANETs). Specifically, we consider four node mobility models: (1) two-dimensional i.i.d. mobility, (2) two-dimensional hybrid random walk, (3) one-dimensional i.i.d. mobility, and (4) one-dimensional hybrid random walk. Two mobility time-scales are investigated in this paper: (i) fast mobility where node mobility is at the same time-scale as data transmissions and (ii) slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions. Given a delay constraint

Impact of Location Popularity on Throughput and Delay in Mobile Ad Hoc Networks

D

Impact of secrecy on capacity in large-scale wireless networks

, we first characterize the optimal multicast capacity for each of the eight types of mobility models, and then we develop a scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor. In addition, we also study heterogeneous networks with infrastructure support.

Asymptotic Analysis on Throughput and Delay in Cognitive Social Networks

With the advent of smart portable devices and location-based applications, users mobility pattern is found to be highly dependent on varying locations. In this paper, we analyze asymptotic throughput-delay performance of mobile ad hoc networks (MANETs) under a location popularity based scenario, where users are more likely to visit popular locations. This work provides a complementary perspective compared with previous studies on fundamental scaling laws for MANETs, mostly assuming that nodes move uniformly in the network. Specifically, we consider a cell-partitioned network model with cells of known popularity, which follows a Zipfs law distribution with popularity exponent α. We first conduct the analysis under traditional store-carry-forward paradigm, and find that location heterogeneity affects the network performance negatively, which is due to the waste of potential transmission opportunities in popular cells. Motivated by this observation, we further propose a novel store-carry-accelerate-forward paradigm to enhance the network communication, exploiting these potential transmissions. Theoretical results demonstrate that our proposed scheme outperforms all delay-capacity results obtained in conventional scheme for any α. In particular, when α = 1, it can achieve a constant capacity with an average delay of Θ(√n) (except for a polylogarithmic factor), while the delay is Θ(n) in conventional scheme. And by letting α = 0, our results can cover Neelys scaling laws. Moreover, we show that the delay-capacity tradeoff ratio satisfies ≥Θ(√n), revealing that exploiting location popularity can effectively improve the performance in MANETs.

The Role of Location Popularity in Multicast Mobile Ad Hoc Networks

Since wireless channel is vulnerable to eavesdroppers, the secrecy during message delivery is a major concern in many applications such as commercial, governmental and military networks. This paper investigates information-theoretic secrecy in large-scale networks and studies how capacity is affected by the secrecy constraint where the locations and channel state information (CSI) of eavesdroppers are both unknown. We consider two scenarios: 1) non-colluding case where eavesdroppers can only decode messages individually; and 2) colluding case where eavesdroppers can collude to decode a message. For the non-colluding case, we show that the network secrecy capacity is not affected in order-sense by the presence of eavesdroppers. For the colluding case, the per-node secrecy capacity of Θ(1/√n) can be achieved when the eavesdropper density ψe(n) is O(n-β), for any constant β >; 0 and decreases monotonously as the density of eavesdroppers increases. The upper bounds on network secrecy capacity are derived for both cases and shown to be achievable by our scheme when ψe(n) = O(n-β) or ψe(n) = Ω(log α-2/α n), where α is the path loss gain. We show that there is a clear tradeoff between the security constraints and the achievable capacity.

Secrecy Capacity Scaling of Large-Scale Networks With Social Relationships

In this paper, we study the throughput and delay in wireless cognitive social networks. Specifically, we consider a common scenario for cognitive radio networks (CRNs) where the primary and secondary networks operate at the same time and space and share the spectrum. On this basis, we integrate a social relationship into the CRN where each source node selects its destination upon a rank-based model, which captures the social characteristic well. By applying a cellular time-division multiple-access scheduling scheme, we first characterize the distinct traffic pattern caused by the social relationships between nodes. Then, we derive the achievable throughput and delay for both primary and secondary networks under the new network setting. In addition, we also study the cognitive social networks with infrastructure where I = o1(n) base stations are regularly deployed within the primary network. Given a probabilistic routing strategy, throughput of the proposed network is recalculated. Particularly, due to the social relationships between nodes, we reveal that a larger I is required if we expect a significant capacity gain within the primary network compared with previous works.

On Multicast Capacity and Delay in Cognitive Radio Mobile Ad Hoc Networks

In the asymptotic analysis of large scale mobile networks, most previous works assume that nodes move in all the cells identically. We put forward this line of research by considering location popularity, which is verified by recent experimental studies. Nodes tend to visit some popular locations and go to other locations less frequently. We first analyze its multicast capacity and delay under the traditional 2-hop store-carry and forward paradigm. With different location popularity distributions, network capacity and delay will vary according to the distribution exponent. As the popularity becomes more diverse, less concurrent transmissions are tolerated in the network, which brings down the performance. Observing that transmission opportunity is not fully utilized in popular cells for 2-hop paradigm, we put forward a 3-hop scheme, which is called store-carry-accelerate-forward scheme. In this 3-hop scheme, each packet is first sent to an initial relay, who carries the packets into the popular cells and then broadcasts to multiple nodes to accelerate the delivery. By so doing, we showed that the 3-hop scheme outperforms the 2-hop scheme for all popularity distributions. Furthermore, we study the delay-capacity tradeoffs for multicast under both schemes and the buffer needed for stability requirement. Our results reveals the joint impact of multicast and location heterogeneity on the design of transmission schemes, and may shed new insights for future studies.