Ns3 Projects

Breadth-first search (BFS) is one of the most common graph traversal algorithms and the building block for a wide range of graph applications. With the advent of graphics processing units (GPUs), several works have been proposed to accelerate graph algorithms and, in particular, BFS on such many-core architectures. Nevertheless, BFS has proven to be an algorithm for which it is hard to obtain better performance from parallelization. Indeed, the proposed solutions take advantage of the massively parallelism of GPUs but they are often asymptotically less efficient than the fastest CPU implementations.

This paper presents BFS-4K, a parallel implementation of BFS for GPUs that exploits the more advanced features of GPU-based platforms (i.e., NVIDIA Kepler) and that achieves an asymptotically optimal work complexity. The paper presents different strategies implemented in BFS-4K to deal with the potential workload imbalance and thread divergence caused by any actual graph non-homogeneity. The paper presents the experimental results conducted on several graphs of different size and characteristics to understand how the proposed techniques are applied and combined to obtain the best performance from the parallel BFS visits. Finally, an analysis of the most representative BFS implementations for GPUs at the state of the art and their comparison with BFS-4K are reported to underline the efficiency of the proposed solution.

Due to energy and bandwidth limitations of wireless sensor networks (WSNs), it is crucial that data provenance for these networks be as compact as possible. Even if lossy compression techniques are used for encoding provenance information, the size of the provenance increases with the number of nodes traversed by the network packets. To address such issues, we propose a dictionary based provenance scheme. In our approach, each sensor node in the network stores a packet path dictionary. With the support of this dictionary, a path index instead of the path itself is enclosed with each packet.

Since the packet path index is a code word of a dictionary, its size is independent of the number of nodes present in the packet’s path. Furthermore, as our scheme binds the packet and its provenance through an AM-FM sketch and uses a secure packet sequence number generation technique, it can defend against most of the known provenance attacks. Through simulation and experimental results, we show that our scheme outperforms other compact provenance schemes with respect to provenance size, robustness, and energy consumption.

One fundamental question for wireless power transfer technology is the energy provisioning problem, i.e., how to provide sufficient energy to mobile rechargeable nodes for their continuous operation. Most existing works overlooked the impacts of node speed and battery capacity. However, we find that if the constraints of node speed and battery capacity are considered, the continuous operation of nodes may never be guaranteed, which invalidates the traditional energy provisioning concept. In this paper, we propose a novel metric-Quality of Energy Provisioning (QoEP)-to characterize the expected portion of time that a node sustains normal operation by taking into account node speed and battery capacity.

To avoid confining the analysis to a specific mobility model, we study spatial distribution instead. As there exist more than one mobility models corresponding to the same spatial distribution, and different mobility models typically lead to different QoEPs, we investigate upper and lower bounds of QoEP in 1D and 2D cases. We derive tight upper and lower bounds of QoEP for 1D case with a single source, and tight lower bounds and loose upper bounds for general 1D and 2D cases with multiple sources. Finally, we perform extensive simulations to verify our theoretical findings.

Trust-based systems have been proposed as means to fight against malicious agents in peer-to-peer networks, volunteer and grid computing systems, among others. However, there still exist some issues that have been generally overlooked in the literature. One of them is the question of whether punishing disconnecting agents is effective. In this paper, we investigate this question for these initial cases where prior direct and reputational evidence is unavailable, what is referred in the literature as trust bootstrapping.

First, we demonstrate that there is not a universally optimal penalty for disconnection and that the effectiveness of this punishment is markedly dependent on the uptime and downtime session lengths. Second, to minimize the effects of an improper selection of the disconnection penalty, we propose to incorporate predictions into the trust bootstrapping process. These predictions based on the current activity of the agents shorten the trust bootstrapping time when direct and reputational information is lacking.

Multi-hop coverage extension can be utilized as a feasible approach to facilitating uncovered users to get Internet service in public area WLANs. In this paper we introduce a relay-union network (RUN), which refers to a public area WLAN in which users often wander in the same area and have the ability to provide data forwarding services for others. We develop a RUN framework to model the cost of providing forwarding services and the utility obtained by gaining services. The objective of the RUN is to maximize the total Quality of Cooperation (QoC) of users in the RUN. Two optimal bandwidth allocation schemes are proposed for both free and dynamic bandwidth demand models.

To make our scheme more pragmatic, we then consider a more practical scenario in which the bandwidth capacity of the relays and the minimum demand of the clients are bounded. We prove that the problems under both the single relay and the multi-relay scenario are NP-hard. Three heuristic algorithms are proposed to deal with bandwidth allocation and relay-client association. We also propose a distributed signaling protocol and divide the centralized MRMC algorithm into three distributed ones to better adapt for real network environment. Finally, extensive simulations demonstrate that our RUN framework can significantly improve the efficiency of cooperation in the long term.