Reliable multi-hop forwarding in vehicular networks is required by many critical intelligent transportation system (ITS) safety applications. Cooperative vehicular multi-hop schemes achieve reliability using broadcast...
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Reliable multi-hop forwarding in vehicular networks is required by many critical intelligent transportation system (ITS) safety applications. Cooperative vehicular multi-hop schemes achieve reliability using broadcast transmissions and multiple forwarding relays at each hop. However, packet duplication must be controlled to circumvent the broadcast storm problem. This paper presents the cooperative POC-based forwarding (CPF) protocol for highway vehicular networks, which extends the repetition-based POC-MAC protocol for multi-hop transmissions. At each forwarding hop, multiple cooperating relays form a virtual relay and schedule their transmissions to correspond to a single POC codeword, thereby adhering to the POC-MAC. CPF exploits spatial diversity while mitigating the effect of hidden terminals. By allocating separate POC-based schedules for multi-hop packets and the periodic broadcast of safety heartbeat packets, the CPF protocol reduces the interference between the two. The performance of the CPF protocol is studied through analysis using a Markov model and through ns-2 simulations.
In dynamic topology of the MANET's nodes are having the high mobility in nature. Because of the dynamic nature of nodes very difficult to find the exact location of node in network for data delivery. Here we propo...
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ISBN:
(纸本)9781479938346
In dynamic topology of the MANET's nodes are having the high mobility in nature. Because of the dynamic nature of nodes very difficult to find the exact location of node in network for data delivery. Here we proposed that to find the exact location of node and ensure the data delivery to destination. In existing system, the location aided routing mechanism where used to find location of node. In this there is load balancing problem and drop tail problem is there. To overcome drop tail problem to implement using the TCP protocol in the geographical routing. Greedy Perimeter Routing protocol which is used to reduce link cost and improve the routing performance. We propose the Adaptive Position Update (APU) strategy for geographic routing, which dynamically adjusts the frequency of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the network. APU is based on two simple principles: 1) nodes whose movements are harder to predict update their positions more frequently (and vice versa), and (ii) nodes closer to forwarding paths update their positions more frequently (and vice versa).
In geographic routing, nodes need to maintain up-to-date positions of their immediate neighbors for making effective forwarding decisions. Periodic broadcasting of beacon packets that contain the geographic location c...
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In geographic routing, nodes need to maintain up-to-date positions of their immediate neighbors for making effective forwarding decisions. Periodic broadcasting of beacon packets that contain the geographic location coordinates of the nodes is a popular method used by most geographic routing protocols to maintain neighbor positions. We contend and demonstrate that periodic beaconing regardless of the node mobility and traffic patterns in the network is not attractive from both update cost and routing performance points of view. We propose the Adaptive Position Update (APU) strategy for geographic routing, which dynamically adjusts the frequency of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the network. APU is based on two simple principles: 1) nodes whose movements are harder to predict update their positions more frequently (and vice versa), and (ii) nodes closer to forwarding paths update their positions more frequently (and vice versa). Our theoretical analysis, which is validated by NS2 simulations of a well-known geographic routing protocol, Greedy Perimeter Stateless Routing protocol (GPSR), shows that APU can significantly reduce the update cost and improve the routing performance in terms of packet delivery ratio and average end-to-end delay in comparison with periodic beaconing and other recently proposed updating schemes. The benefits of APU are further confirmed by undertaking evaluations in realistic network scenarios, which account for localization error, realistic radio propagation, and sparse network.
Beaconless or contention-based geographic routing algorithms forward packets toward a geographical destination reactively without the knowledge of the neighborhood. Such algorithms allow greedy forwarding, where only ...
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Beaconless or contention-based geographic routing algorithms forward packets toward a geographical destination reactively without the knowledge of the neighborhood. Such algorithms allow greedy forwarding, where only the next hop neighbor responds after a timer-based contention using only three messages (RTS, CTS, and DATA) per forwarding step. However, existing contention-based schemes for recovery from greedy failures do not have this property. In this paper, we show that recovery is possible within this 3-message scheme: the Rotational Sweep (RS) algorithm directly identifies the next hop after timer-based contention and constructs a traversal path that ensures progress after a greedy failure. It uses a traversal scheme (called Sweep Circle) that forwards a message along the alpha-shape of the network and provides recovery paths shorter or equal to the prominent face routing with Gabriel graph planarization. An alternative traversal scheme (called Twisting Triangle) provides even shorter routes on average, as shown by simulations. They both also reduce per-node overall network contention delays. We prove that both traversal schemes guarantee delivery in unit disk graphs. Our traversal schemes avoid planarization and are easy to implement, based merely on the evaluation of a function of a neighbor node's relative position. They can also be used for boundary detection and improve path-length in conventional beacon-based routing.
Authenticating spontaneous interactions between devices and users is challenging for several reasons: the wireless (and therefore invisible) nature of device communication, the heterogeneous nature of devices, and lac...
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Authenticating spontaneous interactions between devices and users is challenging for several reasons: the wireless (and therefore invisible) nature of device communication, the heterogeneous nature of devices, and lack of appropriate user interfaces in mobile devices, and the requirement for unobtrusive user interaction. The most promising approach that has been proposed in literature involves the exploitation of the so-called auxiliary channels for authentication to bridge the gap between usability and security. This concept has spawned the independent development of various authentication methods and research prototypes, that, unfortunately, remain hard to compare and interchange and are rarely available to potential application developers. We present a novel, unified cryptographic authentication protocol framework (UACAP) to unify these approaches on using auxiliary channels and analyze its security properties. This protocol and a selection of auxiliary channels aimed at authentication of mobile devices has been implemented and released in an open-source ubiquitous authentication toolkit (OpenUAT). We also present an initial user study evaluating four of these channels.
As the scarce spectrum resource is becoming overcrowded, cognitive radio indicates great flexibility to improve the spectrum efficiency by opportunistically accessing the authorized frequency bands. One of the critica...
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As the scarce spectrum resource is becoming overcrowded, cognitive radio indicates great flexibility to improve the spectrum efficiency by opportunistically accessing the authorized frequency bands. One of the critical challenges for operating such radios in a network is how to efficiently allocate transmission powers and frequency resource among the secondary users (SUs) while satisfying the quality-of-service constraints of the primary users. In this paper, we focus on the noncooperative power allocation problem in cognitive wireless mesh networks formed by a number of clusters with the consideration of energy efficiency. Due to the SUs' dynamic and spontaneous properties, the problem is modeled as a stochastic learning process. We first extend the single-agent Q-learning to a multiuser context, and then propose a conjecture-based multiagent Q-learning algorithm to achieve the optimal transmission strategies with only private and incomplete information. An intelligent SU performs Q-function updates based on the conjecture over the other SUs' stochastic behaviors. This learning algorithm provably converges given certain restrictions that arise during the learning procedure. Simulation experiments are used to verify the performance of our algorithm and demonstrate its effectiveness of improving the energy efficiency.
The dynamic composition of networked appliances, or virtual devices, enables users to generate complex, strong, and specific systems. Current MANET-based composition schemes use service discovery mechanisms that depen...
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The dynamic composition of networked appliances, or virtual devices, enables users to generate complex, strong, and specific systems. Current MANET-based composition schemes use service discovery mechanisms that depend on periodic service advertising by controlled broadcast, resulting in the unnecessary depletion of node resources. The assumption that, once generated, a virtual device is to remain static is false;the device should gracefully degrade and upgrade along with the conditions in the user's environment, particularly the network's current performance requirements. Presently, schemes for infrastructure-less virtual device composition and management do not consider this adaptation. We present a distributed constraint satisfaction problem (distCSP) for virtual device composition in MANETs that addresses these issues together with simulations that show its effectiveness and efficiency.
With the advances of communications, computing, and positioning technologies, mobile devices have been regarded as mobile computing platforms for various kinds of location-based and human-computation services. However...
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With the advances of communications, computing, and positioning technologies, mobile devices have been regarded as mobile computing platforms for various kinds of location-based and human-computation services. However, most existing applications regard each device as a sensor or focus on services with the computation on a single device. In contrast, this paper leverages a group of mobile devices as a collaborative and distributed search platform. Specifically, we propose a search system with mobile devices for rescue and patrol operations. The system utilizes mobile devices to find and assign the search route to each searcher in a collaborative and distributed manner. Given the roads to be searched in an area and the candidate start locations, our system minimizes the time required to search the whole area and guarantees that each road will be searched at least once. We first formulate the k-Person Search Problem for k mobile devices and prove that the problem is NP-Hard. To find the optimal solutions, we propose a centralized algorithm for a special case and an Integer Linear Programming formulation for general cases. We also devise an approximation algorithm. The algorithms can be used to dispatch the searchers before the operation starts. Moreover, to support online adaptation, we formulate the Path Refinement Problem for path exchange among searchers and propose a distributed algorithm to adaptively adjust the paths after the search starts. We also implement the proposed algorithms in mobile devices as a collaborative and distributed search system and demonstrate the efficiency of our algorithms with computation simulations and field trials.
This paper presents a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions by leveraging the local decisions reported by their neighbors. This detection scheme can handle...
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This paper presents a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions by leveraging the local decisions reported by their neighbors. This detection scheme can handle cases where nodes have different accuracy levels. The derived fault-tolerant estimator is proven to be optimal under the maximum a posteriori (MAP) criterion. An equivalent weighted voting scheme is also derived. Further, two new error models are derived to take into account the neighbor distance and the geographical distributions of the two decision quorums. These models are particularly suitable for detection applications where the event under consideration is highly localized. The fault-tolerant estimator is simulated using a network of 1,024 nodes deployed randomly in a square region and assigned random probabilities of failure. Several estimation schemes that allow nodes to learn their error rates continuously are developed. These error rates are used in the distributed estimation schemes to assign appropriate weights to the nodes in the voting scheme.
This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP Long-Term Evolution (LTE) do...
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This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP Long-Term Evolution (LTE) downlink. We impose the LTE MIMO constraint of selecting only one MIMO mode (spatial multiplexing or transmit diversity) per user per transmission time interval (TTI). First, we address the optimal MIMO mode selection (multiplexing or diversity) per user in each TTI in order to maximize the proportional fair (PF) criterion adapted to the additional frequency and spatial domains. We prove that both single-user (SU-) and multi-user (MU-) MIMO FDPS problems under the LTE requirement are NP-hard. We therefore develop two types of approximation algorithms (ones with full channel feedback and the others with partial channel feedback), all of which guarantee provable performance bounds for both SU- and MU-MIMO cases. Based on 3GPP LTE system model simulations, our approximation algorithms that take into account both spatial and frequency diversity gains outperform the exact algorithms that do not exploit the potential spatial diversity gain. Moreover, the approximation algorithms with partial channel feedback achieve comparable performance (with only 1-6 percent performance degradation) to the ones with full channel feedback, while significantly reducing the channel feedback overhead by nearly 50 percent.
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