Amit Dvir

Backpressure-based routing protocol for DTNs

In this paper we consider an alternative, highly agile In this paper we consider an alternative, highly agile approach called backpressure routing for Delay Tolerant Networks (DTN), in which routing and forwarding decisions are made on a per-packet basis. Using information about queue backlogs, random walk and data packet scheduling nodes can make packet routing and forwarding decisions without the notion of end-to-end routes. To the best of our knowledge, this is the first ever implementation of dynamic backpressure routing in DTNs. Simulation results show that the proposed approach has advantages in terms of DTN networks.

Automated antenna positioning algorithms for wireless fixed-access networks

Abstract This article addresses a real-life problem - obtaining communication links between multiple base station sites, by positioning a minimal set of fixed-access relay antenna sites on a given terrain. Reducing the number of relay antenna sites is considered critical due to substantial installation and maintenance costs. Despite the significant cost saved by eliminating even a single antenna site, an inefficient manual approach is employed due to the computational complexity of the problem. From the theoretical point of view we show that this problem is not only NP hard, but also does not have a constant approximation. In this paper we suggest several alternative automated heuristics, relying on terrain preprocessing to find educated potential points for positioning relay stations. A large-scale computer-based experiment consisting of approximately 7,000 different scenarios was conducted. The quality of alternative solutions was compared by isolating and displaying factors that were found to affect the standard deviation of the solutions supplied by the tested heuristics. The results of the simulation based experiments show that the saving potential increases when more base stations are needed to be interconnected. The designs of a human expert were compared to the automatically generated solutions for a small subset of the experiment scenarios. Our studies indicate that for small networks (e.g., connecting up to ten base stations), the results obtained by human experts are adequate although they rarely exceed the quality of automated alternatives. However, the process of obtaining these results in comparison to automated heuristics is longer. In addition, when more base station sites need to be interconnected, the human approach is easily outperformed by our heuristics, both in terms of better results (fewer antennas) and in significant shorter calculation times.

SPLAST: a novel approach for multicasting in mobile wireless ad hoc networks

Trees of special properties are required to provide efficient network management of group communications in mobile ad hoc networks. Usually, such trees try to balance between the requirements to minimize the total tree cost and the requirement to minimize the maximal shortest path. This work presents a novel solution for efficient multicast trees that fulfill both requirements called SPLAST. The following discussion covers the development process, starting from centralized static solution, through distributed implementation to a complete distributed algorithm that cope with various scenarios that are relevant to wireless ad hoc networks by efficient management and maintenance of the underlying components of the algorithm. Simulation inquiry shows that the average performance of SPLAST is attractive as well.

Centdian Computation in Cactus Graphs

This paper focuses on the centdian problem in a cactus network where a cactus network is a connected undirected graph, and any two simple cycles in the graph have at most one node in common. The cactus network has important applications for wireless sensor networks when a tree topology might not be applicable and for extensions to the ring architecture. The centdian criterion represents a convex combination of two QoS requirements: transport and delay. To the best of our knowledge, no efficient algorithm has yet been developed for constructing a centdian node in a cactus graph, either sequential or distributed. We first investigate the properties of the centdian node in a cycle graph, and then explore the behavior of the centdian node in a cactus graph. Finally, we present new efficient sequential and distributed algorithms for finding all centdian nodes in a cycle graph and a cactus graph.

Placing and maintaining a core node in wireless ad hoc sensor networks

Wireless Ad hoc sensor networks are characterized by several constraints, such as bandwidth, delay, power, etc. These networks are examined by constructing a tree network. A core node usually chosen to be the median or center of the multicast tree network with a tend to minimize a performance metric, such as delay or bandwidth. In this paper, we present new efficient strategy for constructing and maintaining a core node in multicast tree for wireless ad hoc sensor networks that undergo dynamic changes based on local information. The new core (centdian) function is defined by convex combination that signifies total bandwidth and delay constraints. We provide two bounds of O(d) and O(d + l) time for maintaining the centdian using local updates, where l is the hop count between the new center and the new centdian and d is the diameter. We also show a O(n log n) time solution for finding centdian in the Euclidian complete network using interesting observations. Finally a simulation is presented.

Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

The increasing demand for video streaming services with a high Quality of Experience (QoE) has prompted considerable research on client-side adaptation logic approaches. However, most algorithms use the client’s previous download experience and do not use a crowd knowledge database generated by users of a professional service. We propose a new crowd algorithm that maximizes the QoE. We evaluate our algorithm against state-of-the-art algorithms on large, real-life, crowdsourcing datasets. There are six datasets, each of which contains samples of a single operator (T-Mobile, AT&T or Verizon) from a single road (I100 or I405). All measurements were from Android cellphones. The datasets were provided by WeFi LTD and are public for academic users. Our new algorithm outperforms all other methods in terms of QoE (eMOS).

A novel multicast adaptive logic for dynamic adaptive streaming over HTTP network

Video streaming is now responsible for the majority of Internet traffic and is expected to keep growing over the coming years. Dynamic Adaptive Streaming over HTTP (DASH) [1] is an ISO/IEC MPEG multi-quality layer streaming solution that is designed to enable interoperability between servers and clients of different vendors. In the DASH protocol, the client-side player is assumed to have Adaptation Logic (AL). The AL evaluates the various video representation segments available on the server and chooses the most suitable segments balancing between video quality and switching time. Note that dynamic adaptation is necessary due to the fact that the network bandwidth (e.g. cellular network) and the users buffer are not stable and have a high influence on re-buffering. However, to date, none of the research considers multicast conditions and therefore, there is no AL specifically designed to support multicast at the client side. In this paper, we present the Harmonic Mean Adaptive Logic (HMAL) which is a buffer sensitive adaptation logic that first calculates how many segments exist in the buffer and then estimates the channel bandwidth using the harmonic mean of the previous n samples. The HMAL is designed to support multicast networks by reducing the weights of hight quality segments in the bandwidth estimation and give more weight to lower quality segments. Compared to the multicast versions of well known ALs, the simulation results showed that HMAL has the best bandwidth estimation, the lowest number of re-buffering events, and the highest buffer efficiency.

SDTP+: Securing a distributed transport protocol for WSNs using Merkle trees and Hash chains

Transport protocols for Wireless Sensor Networks (WSNs) are designed to fulfill both reliability and energy efficiency requirements. Distributed Transport for Sensor Networks (DTSN) [1] is one of the most promising transport protocols designed for WSNs because of its effectiveness; however, it does not address any security issues, hence it is vulnerable to many attacks. The first secure transport protocol for WSN was the secure distributed transport protocol (SDTP) [2], which is a security extension of DTSN. Unfortunately, it turns out that the security methods provided by SDTP are not sufficient; some tricky attacks get around the protection mechanism. In this paper, we describe the security gaps in the SDTP protocol, and we introduce SDTP+ for patching the weaknesses. We show that SDTP+ resists attacks on reliability and energy efficiency of the protocol, and also present an overhead analysis for showing its effectiveness.

Multicast adaptive logic for Dynamic Adaptive Streaming over HTTP network

Video streaming constitutes the vast majority of Internet traffic and the DASH protocol has become the de-facto standard in the industry of multimedia delivery. The multicast method for information distribution has the potential to dramatically reduce multimedia streaming traffic; however, to date, there is no effective Adaptive Logic (AL) designed to support multicast constraints at the client side. In this paper we present an adaptive logic that is designed specifically for multicast scenarios. A comparison of our Multicast Adaptive Logic (MAL) with leading ALs under multicast conditions demonstrates that MAL provides the best performance under multicast conditions and good performance under unicast conditions.

Analysis and optimization of live streaming for over the top video

Video has become an integral part of the Internet user content. The use of High Definition (HD) video content increases the bandwidth requirements of the Internet infrastructure. Moreover, rapid increase in the Over-the-Top (OTT) Internet video bandwidth consumption has major impact on the business models of the Internet Service Providers (ISP). To support the ever-growing demand for IP-based video, two major technologies are used: Peer-to-Peer (P2P) for live video and Multi-Layer Cache (MLC) for fully-stored video content. In this paper we focus on partial streaming, which is a ‘semi-live’ form of video delivery of live events such as sports, concerts, and news in the Video-on-Demand (VOD) format. The VOD supports user control features such as Start Over, Pause, Rewind, and Forward. We suggest a new framework for optimizing partial streaming using MLC, which allows storing partial video content in the time-based chunks of data (that is, data packets) while forwarding these data chunks to the users at various levels of ISP networks. The suggested framework may be helpful for solving the OTT bottleneck caused be video streaming.