Average Download Research Articles

Content Placement and User Association for Delay Minimization in Small Cell Networks

In small cell networks, content placement can reduce the content download delay at backhaul links while imposing challenges on user association problems. Specifically, a user may be associated with a small base station (SBS) that has the desired contents but is far away, increasing the delay over radio access links. To this end, we investigate the joint content placement and user association problem to reduce the average download delay over backhaul and radio access links for content delivery. Considering both dynamic user population and natural tandem systems, we model content delivery in each SBS as a tandem queue and thus derive the average sojourn time (the average time contents stay in the tandem queue), i.e., the average download delay. On this basis, we formulate a delay minimization problem, encompassing user characteristics (traffic arrival rates, requested content lengths and content preferences) and SBS constraints (backhaul capacity and storage size). Then, this problem is decomposed into a user association subproblem and a content placement subproblem by exploiting the biconvexity. Finally, a distributed content placement and user association scheme is proposed by exploring the optimal match with the first derivative length method. Extensive simulation results reveal that the delay under the proposed content placement policy may be reduced as user characteristics become heterogeneous, which is opposite to the case under user association policies.

Performance analysis of video on demand in an IEEE 802.11p-based vehicular network

We consider a VoD (Video on-Demand) platform designed for vehicles traveling on a highway or other major roadway. Typically, cars or buses would subscribe to this delivery service so that their passengers get access to a catalog of movies and series stored on a back-end server. The network infrastructure comprises IEEE 802.11p RSUs (Road Side Units) that are deployed along the highway and deliver video content to traveling vehicles. In this paper, we propose a simple analytical and yet accurate solution to estimate two key performance parameters for a VoD platform: (i) the average download data rate experienced by vehicles over their journey and (ii) the average “interruption time”, which corresponds to the fraction of time the video playback of a given vehicle is interrupted because of an empty buffer. Through multiple examples, we investigate the influence of several parameters (e.g., the video bit rate, the number of vehicles, the distance between RSUs, the vehicle velocity) on these two performance parameters whose outcome may help the sizing of an IEEE 802.11p-based VoD platform.

Caching mechanism for mobile edge computing in V2I networks

AbstractThe caching‐enabled mobile edge computing (MEC) system becomes increasingly crucial to the future long‐term evolution vehicle‐to‐infrastructure (LTE‐V2I) network, especially for fast delivery of popular content of delay‐sensitive applications in the backhaul capacity–limited vehicular networks. Most related studies mainly focus on computation offloading strategy design and coding caching, while the deployment strategy design of caching capacities for high‐speed vehicles has been overlooked. In this paper, we investigate the deployment problem in LTE‐V2I networks with particular consideration on high‐speed vehicles. First, in a one‐way scenario, a joint optimization framework is formulated to minimize the cache size of the MEC system, meanwhile maximizing the average downloading percentage, where the MEC system's backhaul capacities, vehicle speeds, content popularity distributions, and sides of the highway are taken into account. The impacts of LTE‐V2I system parameters, eg, vehicle speed, on the objective function are revealed through the one‐way optimization. Then, the two‐way optimization is formulated and solved by developing an iterative optimization approach based on the aforementioned one‐way scenario. Particularly, the optimal caching allocation between two ways is derived. Simulation results validate the effectiveness of the proposed approaches even with low backhaul capacities and high vehicle speed.

A parallel optimization for energy and robustness of file distribution services

This paper focuses on the energy consumption of content distribution and sharing services that have a significant percentage of traffic on the Internet today. Taking the “energy saving” and “network robustness in traditional traffic engineering” as the dual optimization objects, a weighted green factor is introduced and an optimization model called ETE-FD (Energy-Aware Traffic Engineering File Distribution) is established. The model takes into account the overlay layer and the network layer, end systems and routing nodes. A multi-machine parallel algorithm based on dual decomposition and subgradient projection is proposed. Even with more than 1000 nodes, the solution process is still fast. However, when the number of nodes exceeds 3000, the time complexity is not ideal. On this basis, we continue to improve the computational efficiency of the subgradient projection method: using the deflection subgradient to reduce the number of iterations, and introducing the GPU (Graphics Processing Unit) to speed up the calculation, thereby greatly reducing the calculation time. The effectiveness of the model was verified by simulation experiments. Experimental results show that the adjustable range of the ETE-FD model is significant. From the performance-oriented to the energy-oriented adjustment process, the energy consumption of the whole system was reduced by 47.09%, but the reliability of the network was also reduced by 58.18%, and the average download time increased by 90%. The EOCFD (Energy-optimal Collaborative File Distribution) model of the same kind of research also proposes a file distribution scheduling mechanism to save energy by reducing the total time that the hosts receive files. Compared with the EOCFD scheme, the ETE-FD’s power consumption is reduced by about 10.8% compared to the pure energy-saving optimization. If set to only the reliability optimization goal measured by MLU (Maximum Link Utilization), it is about 43.9% higher than EOCFD.

Sporadic Cloud-Based Mobile Augmentation on the Top of a Virtualization Layer: A Case Study of Collaborative Downloads in VANETs

Current approaches to Cloud-based Mobile Augmentation (CMA) leverage (cloud-based) resources to meet the requirements of rich mobile applications, so that a terminal (the so-called application node or AppN) can borrow resources lent by a set of collaborator nodes (CNs). In the most sophisticated approaches proposed for vehicular scenarios, the collaborators are nearby vehicles that must remain together near the application node because the augmentation service is interrupted when they move apart. This leads to disruption in the execution of the applications and consequently impoverishes the mobile users’ experience. This paper describes a CMA approach that is able to restore the augmentation service transparently when AppNs and CNs separate. The functioning is illustrated by a NaaS model where the AppNs access web contents that are collaboratively downloaded by a set of CNs, exploiting both roadside units and opportunistic networking. The performance of the resulting approach has been evaluated via simulations, achieving promising results in terms of number of downloads, average download times, and network overhead.

A Network-Coded Caching-Based Multicasting Scheme for Information-Centric Networking (ICN)

Information-centric networking (ICN) is gradually becoming an alternative approach to the conventional Internet architecture through the distribution of enlightening information (named as content) on the Internet. Given the growing Internet traffic, the adapted information-centric architecture is expected to more favourably serve the user’s need of accessing data. In this paper, we proposed a novel framework for cache management in ICN that jointly considers the caching strategy and network coding. For the proposed cache management framework, we first evaluated a new Centrality-measures to assess the variation in the behaviour of each node in the network and to identify such behaviour. Subsequently, we developed an efficient random network coding-based cache management algorithm to obtain a support for caching and multicasting in the ICN paradigm. Extensive simulations were made, and related results showed that our proposed scheme has better performance in terms of cache hit ratio, average download time, server hit reduction ratio, and traffic overhead compared with other schemes in our simulated scenarios.

Node importance to community based caching strategy for information centric networking

SummaryInformation Centric Networking (ICN) is a novel future network architecture that is focusing on content distribution. Its ubiquitous caching schemes can improve network performance. In this paper, we propose a node importance to community based caching scheme with network coding in ICN, which is named as NICNC. For each community, content router makes cache decision depending on its node importance to community to make content cached more reasonable in temporal and spatial distribution. Moreover, by applying network coding into ICN, one coded blocks containing information of multiple chunks can satisfy multiple interests for different chunks sent by different consumers. This can significantly enhance cache diversity and cache hit rate without increasing cache capacity. Experimental results show that our scheme can improve the network performance at many aspects, such as average download time, cache hit rate, and instantaneous hop reduction rate.

Network-Coding Approach for Information-Centric Networking

The current internet architecture is inefficient in fulfilling the demands of newly emerging internet applications. To address this issue, several over-the-top application-level solutions have been employed, making the overall architecture very complex. Information-centric-networking (ICN) architecture has emerged as a promising alternative solution. The ICN architecture decouples the content from the host at the network level and supports the temporary storage of content in an in-network cache. Fundamentally, the ICN can be considered a multisource, multicast content-delivery solution. Because of the benefits of network coding in multicasting scenarios and proven benefits in distributed storage networks, the network coding is apt for the ICN architecture. In this study, we propose a solvable linear network-coding scheme for the ICN architecture. We also propose a practical implementation of the network-coding scheme for the ICN, particularly for the content-centric network (CCN) architecture, which is termed the coded CCN. The performance results show that the network-coding scheme improves the performance of the CCN and significantly reduces the network traffic and average download delay.

An An efficient adaptive neuro-fuzzy system based attack detection technique for VANETs

Vehicular Ad-hoc Networks (VANETs) are generally accepted as an exceptional type of Mobile Ad hoc Network (MANET). VANETs have seen tremendous growth in last decade, providing a vast range of uses in both military as well as civilian activities. The temporary connectivity in the vehicles can also increase the driver's capability on the road. In this paper, an efficient data dissemination approach is proposed which not only improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The effectiveness of the proposed approach is demonstrated when it comes to the significant gets achieved in the parameters namely, end to end delay, packet loss ratio, average download delay and throughput in comparison with the existing approaches.

MeNTor: A wireless-mesh-network-aware data dissemination overlay based on BitTorrent

IEEE 802.11s introduces MAC-layer extensions to enable vendor-independent and inter-operable WLAN mesh networks. Featuring automatic device interconnection and routing, 802.11s networks provide a higher scalability, flexibility, and robustness compared to common centralized WLAN infrastructures. As logical Peer-to-Peer (P2P) networks exhibit many of the characteristics of physical WLAN mesh networks on the application layer, it is obvious to consider solutions where both technologies interact to leverage robust distributed wireless applications, such as collaborative data distribution and synchronization in future smart cities. Envisioned scenarios include the administration and update deployment to specific device groups or the distributed caching and delivery of on-demand multi-media content to selected end points within a city-area wireless mesh network. Nevertheless, common P2P protocols, such as BitTorrent (BT), do not consider the structure of the physical underlay as they were primarily designed to be used over wired communication networks, such as large parts of the Internet. Hence, the default BT peer selection mechanism does not adapt to the network topology and varying medium utilization in wireless multi-hop networks. We present MeNTor, a set of optimizations to enable underlay-aware BT peer selection in WLAN mesh networks. It relies on cross-layer integration of default 802.11s information, only requiring minor extension of the BT application layer without introducing any MAC-layer modifications or traffic overhead. Our solution was evaluated in a 25-node real-world mesh test bed, using 10 different seed/leecher placements and comparing 18 parameter combination variants of MeNTor. Results show that average download times can be reduced by 30–40%, depending on the seed/leecher placement and parameter combination variant. Finally, we recommend the variant that performed best across all scenarios as prospective default configuration.

Socially Aware Caching Strategy in Device-to-Device Communication Networks

As a response to the challenge of data traffic explosion in wireless networks, content caching in device-to-device (D2D) communication networks has emerged as a promising solution. However, in practical deployment, D2D content caching has its own problems. In particular, not all of the user devices are willing to share the content with others due to numerous concerns, such as security, battery life, and social relationship. In this paper, we consider the factor of social relationship in the deployment of D2D content caching. First, we apply stochastic geometry theory to derive an analytical expression of downloading performance for the D2D caching network. Specifically, a social relationship model with respect to the physical distance is adopted in our analysis to obtain the average download delay performance using random and deterministic caching strategies. Second, to achieve a better performance in more practical and specific scenarios, we develop a socially aware distributed caching strategy based on a decentralized learning automaton, to optimize the cache placement operation in D2D networks. Different from the existing caching schemes, the proposed algorithm not only considers the file request probability and the closeness of devices as measured by their physical distance but also takes into account the social relationship between D2D users. Our simulation results show that the proposed algorithm can converge quickly and outperforms the random and deterministic caching strategies. With these results, our work sheds insights on the design of D2D caching in the practical deployment of 5G networks.

PCLNC: A low-cost intra-generation network coding strategy for P2P content distribution

It has been proven that network coding can provide significant benefits to P2P networks. In recent years, many schemes have been designed to provide low-cost network coding strategies for P2P content distribution systems. In this paper, firstly, we propose a low-cost intra-generation network coding strategy. By designing the upper triangular encoding matrix, we can reduce the computational complexity of encoding and decoding. Secondly, a linear dependency detection method for encoded blocks is proposed. We use the postponement strategy and the loop self-checking strategy to reduce the probability of receiving linearly dependent encoded blocks. At last, we simulate the distribution system using the above strategies on the simulator and compare it to other systems. From the simulation results, the performance of our system is better than that of the other two systems. Taking the average download time as an example, the average download time of our system is 21.0% and 3.17% lower than other schemes respectively, which effectively improves the distribution efficiency.

The case for HTTPS: measuring overhead and impact of certificate authorities

The popularity of the web is indisputable. With revelations about mass surveillance, the use of secure web through TLS connections is needed for privacy. However, the pushback against enabling secure web connections by default is due to increase in communication time. We quantify the communication time for HTTP and HTTPS download times for the most popular websites. The average download time over a HTTP connection is 2.604 seconds while the average download time over a HTTPS connection is 2.937 seconds. The overhead in using encryption is 333 milliseconds (about three roundtrip times on the internet) or 333/2,604 = 12.78%. We thus make the case that HTTPS should be enabled by default due to the low communications overhead. With the recent hacks at certificate authorities, we also quantify which certificate authorities are most popular on the internet. By trusting ten certificate authorities, a web browser can access almost 80% of HTTPS websites.

Content Cache Placement for Scalable Video in Heterogeneous Wireless Network

To alleviate the pressure brought by the explosion of mobile video traffic on present cellular networks, small cell base stations (SBSs) with caching ability are introduced. In this letter, we consider the caching strategy of scalable video coding streaming over heterogeneous wireless network containing SBSs. We formulate an integer programming problem to minimize the average download time under the constraint of cache size at each SBS, and show that finding the optimal caching placement strategy is NP-hard. Heuristic solution was proposed based on the convex programming relaxation, which reveals the structural properties of cache allocation for each video. Simulation results demonstrate that our proposed caching strategies acquire significant performance gain compared with conventional caching policy.

Broadband or bust

Circle. Engines roaring, Annie pauses to steady its load, which had begun to sway below, and veers off toward a bald mountaintop. On the mountain, at a rocky site called Igichuk, a work crew has just finished setting up the tower’s base, dropped off earlier by Annie. Now, they’re focused on executing the most delicate delivery of the day, one of many difficult steps required to sink a single new telecommunications tower into the vast, roadless Alaskan tundra. When Annie arrives, the pilot carefully dangles the new section of tower above its base. Below, four crew members stand ready to guide it into position, strapped into harnesses with their feet braced against the base’s highest rung. Once the new section of tower is close enough, each crew member grabs a steel rope looped through one of its lowest joints and gently nudges the tower so that it is centered directly over the base. Within minutes, the section is lined up, its four metal feet perfectly aligned with the base’s corners. The crew works quickly to insert a single bolt into each leg; they’ll go back and add more later. When they give the sign, the pilot releases the tower from Annie’s grasp, and pulls away. The tower stands, now the highest point across the tundra, and sparkles in the midday sun. Once active, it will relay data north to several hundred miners at Red Dog, the world’s largest zinc mine, and back to a tower in Kotzebue, a city of 3,245 built on a thin lip of spongy land that bows out into the Chukchi Sea along the isolated western rim of Alaska. Here on the edge of the U.S. Arctic, Internet connectivity is a slow—and expensive—proposition. Eighty-one percent of rural residents in Alaska do not have broadband Internet, defined by the U.S. Federal Communications Commission (FCC) as providing a minimum download speed of 25 megabits per second. People in Kotzebue have long relied on satellite connections for Internet service at speeds comparable to those of dial-up. At the beginning of the year, their average download speed was just 2 Mb/s. The Igichuk tower is one of the final pieces of one of the most ambitious telecommunications projects in the rural United States. Built by General Communication Inc. (GCI) and known as TERRA, it was completed this past October, after US $300 million of investment and six years of construction, when engineers installed its final microwave repeater. The network uses a combination of repeater data links and fiber optics h u l k i n g o r a n g e h e l i c o p t e r n a m e d A n n i e h o i s t s a g l e a m i n g m e t a l t o w e r i n t o t h e s k y o n t h e o u t s k i r t s o f K o t z e b u e , a s m a l l A l a s k a n

Cache Placement in Fog-RANs: From Centralized to Distributed Algorithms

To deal with the rapid growth of high-speed and/or ultra-low latency data traffic for massive mobile users, fog radio access networks (Fog-RANs) have emerged as a promising architecture for next-generation wireless networks. In Fog-RANs, the edge nodes and user terminals possess storage, computation and communication functionalities to various degrees, which provides high flexibility for network operation, i.e., from fully centralized to fully distributed operation. In this paper, we study the cache placement problem in Fog-RANs, by taking into account flexible physical-layer transmission schemes and diverse content preferences of different users. We develop both centralized and distributed transmission aware cache placement strategies to minimize users' average download delay subject to the storage capacity constraints. In the centralized mode, the cache placement problem is transformed into a matroid constrained submodular maximization problem, and an approximation algorithm is proposed to find a solution within a constant factor to the optimum. In the distributed mode, a belief propagation based distributed algorithm is proposed to provide a suboptimal solution, with iterative updates at each BS based on locally collected information. Simulation results show that by exploiting caching and cooperation gains, the proposed transmission aware caching algorithms can greatly reduce the users' average download delay.

RSNC-based Mechanism against Content Pollution Attack Method in NDN

Network coding facilitates content distribution for named data networking (NDN), which improves the cache hit ratio, decreases average download time and reduces transmission amount. However, NDN is likely to cause content pollution attacks because of the cache mechanism and network coding. Request-specific network coding (RSNC) is a new class of network coding mechanism, by introducing the homomorphic hash mechanism, and this paper proposes a new method based on RSNC mechanism against content pollution attack in NDN. The new method, firstly, ensures consumers receiving linear independent coding blocks by using RSNC. Secondly, the content server adopts content-chunk-based transmission mechanism, and binds the name and content by homomorphic signing the transferred content blocks and names. Thirdly, using dynamic public key technique, our scheme authenticates each generation without updating the initial secret key. Finally, using homomorphic hash can verify the signature receives by intermediate nodes or the destination nodes. By security analysis and proof, the new method can resist the content pollution attack in the named data networking while guaranteeing the network performance and resist the Intra/Inter-GPAs at the same time.

Energy-Efficient Caching for Mobile Edge Computing in 5G Networks

Mobile Edge Computing (MEC), which is considered a promising and emerging paradigm to provide caching capabilities in proximity to mobile devices in 5G networks, enables fast, popular content delivery of delay-sensitive applications at the backhaul capacity of limited mobile networks. Most existing studies focus on cache allocation, mechanism design and coding design for caching. However, grid power supply with fixed power uninterruptedly in support of a MEC server (MECS) is costly and even infeasible, especially when the load changes dynamically over time. In this paper, we investigate the energy consumption of the MECS problem in cellular networks. Given the average download latency constraints, we take the MECS’s energy consumption, backhaul capacities and content popularity distributions into account and formulate a joint optimization framework to minimize the energy consumption of the system. As a complicated joint optimization problem, we apply a genetic algorithm to solve it. Simulation results show that the proposed solution can effectively determine the near-optimal caching placement to obtain better performance in terms of energy efficiency gains compared with conventional caching placement strategies. In particular, it is shown that the proposed scheme can significantly reduce the joint cost when backhaul capacity is low.

Interference-constrained routing over P2P-share enabled multi-hop D2D networks

The exponentially-increasing demands on ubiquitous information exchange have inspired wide research interests and efforts on the 5th Generation (5G) of mobile communications system. Among diverse cutting-edge revolutionary technologies towards 5G networks, device-to-device (D2D) networks, where device nodes can communicate with each other by reusing the cellular network’s spectrum in an underlay fashion. We in this paper propose the interference-constrained routing schemes over peer-to-peer (P2P) share enabled multi-hop D2D networks, where multiple D2D subscribers attempt to download the common data from multiple distributed D2D servers. In particular, we aim at optimizing the average download rate over subscribers subject to the interference constraint for cellular network’s spectrum. We first focus on a typical case with two subscribers, two file servers, and two cellular users. We propose a Routing scheme with Direct P2P-Share (R-DPS), which allows subscribers to distribute their received data to each other via a detoured route. To offer better performances, we develop an improved Routing scheme, named Coverage-based P2P-Share (R-CPS). The R-CPS scheme can effectively make use of the broadcast nature of wireless channels to assure that each selected route can cover the other subscriber, rather than directly pass through them in the R-DPS scheme. We further study the generalized case where the number of subscribers, servers, and cellular users can be arbitrary. Particularly, we propose a Routing scheme with Location-Aware P2P-Share (R-LPS) mechanism, the core idea of which is to find a route passing by or directly through other subscribers. Simulation evaluations demonstrate that our proposed R-DPS and R-CPS schemes for the two-subscriber case and the R-LPS scheme for the generalized case all have the capability to effectively improve the data download rate as compared to the approach without enabling P2P support.

CCN에서 정보제공자의 이동성 지원을 위한 푸싱 기법

CCN(Content-Centric Network) enables users to retrieve content using the content's name. Researchers face critical challenges in terms of mobility. Since the routing information is part of the content name, when the provider moves, it is necessary to update all the routers routing information. However, this requires significant costs. In this paper, we propose PNPCCN(Proactive Neighbor Pushing CCN), considering the popularity and rarity of mobility support, for providers in CCN environments. Via simulation studies, we demonstrate that our solutions are effective in terms of shorter numbers of retransmitted Interest packets, and average download times and higher delivery ratios during mobility.