Wenjing Wang

Small-Scale and Large-Scale Routing in Vehicular Ad Hoc Networks

A vehicular ad hoc network (VANET) is a highly mobile wireless ad hoc network that is targeted to support vehicular safety, traffic monitoring, and other applications. Mobility models used in traditional mobile ad hoc networks cannot directly be applied to VANETs since real-world factors such as road layouts and traffic regulations are not considered. In this paper, we propose a vehicular mobility model that reflects real-world vehicle movement and study the performance of packet-routing protocols. First, we study the routing in small-scale VANETs and propose two routing schemes: (1) connection-based restricted forwarding (CBRF) and (2) connectionless geographic forwarding (CLGF). With the insights obtained, we consider routing in large-scale VANETs. Since road complexity and traffic variety may cause many potential problems that existing routing protocols cannot address, we introduce a two-phase routing protocol (TOPO) that incorporates road map information. The proposed protocol defines an overlay graph with roads of high vehicular density and access graphs that are connected to the overlay. While in the overlay, packets are forwarded along a precalculated path. As far as access routing is concerned, we employ the aforementioned CBRF and CLGF schemes and send packets to the overlay or handle packets delivered from the overlay. We argue that the TOPO can serve as a framework that integrates existing VANET routing protocols. We also consider data diversity in VANETs and design the TOPO as an intelligent transportation system (ITS)-friendly protocol. To validate our design philosophy and the routing protocol, we use different areas in the city of Orlando, FL, and generate vehicular mobility traces, following our mobility models. We feed the traces to network simulators and study the routing behavior. Simulation results demonstrate the performance and effectiveness of the proposed routing protocols for large-scale VANET scenarios.

Coexistence with malicious nodes: A game theoretic approach

In this paper, we use game theory to study the interactions between a malicious node and a regular node in wireless networks with unreliable channels. Since the malicious nodes do not reveal their identities to others, it is crucial for the regular nodes to detect them through monitoring and observation. We model the malicious node detection process as a Bayesian game with imperfect information and show that a mixed strategy perfect Bayesian Nash Equilibrium (also a sequential equilibrium) is attainable. While the equilibrium in the detection game ensures the identification of the malicious nodes, we argue that it might not be profitable to isolate the malicious nodes upon detection. As a matter of fact, malicious nodes and regular nodes can co-exist as long as the destruction they bring is less than the contribution they make. To show how we can utilize the malicious nodes, a post-detection game between the malicious and regular nodes is formalized. Solution to this game shows the existence of a subgame perfect Nash Equilibrium and the conditions that achieve the equilibrium. Simulation results and their discussions are also provided to illustrate the properties of the derived equilibria.

An Integrated Study on Mobility Models and Scalable Routing Protocols in VANETs

A vehicular ad hoc network (VANET) is a high mobility wireless ad hoc network that is targeted to support vehicular safety, traffic monitoring, and other commercial applications. Mobility models used in traditional mobile ad hoc networks cannot be directly applied to VANETs since real world factors such as road layouts and traffic regulations are not considered. In this paper, we propose a vehicular mobility model that reflects real world vehicle movement on the road. Based on the mobility, we study the performance of existing Mobile Ad Hoc network (MANET) routing protocols, i.e., AODV and GPSR. We observe the drawbacks of the MANET protocols and argue the inappropriateness of directly applying those MANET protocols to VANETs. We also propose simple modifications to these protocols which make them more suitable for small scale VANETs. When investigating the large scale VANETs, we introduce a two phase routing protocol that incorporates map information. The proposed protocol defines an overlay graph with roads of high vehicular density and forwards packet along the pre-calculated path in the overlay. The access, which is the rest areas relies on our modified small scale routing protocols to send packets to overlay . Both small and large scale routing protocols are validated with simulation. We generate vehicular mobility traces for different road layouts in Orlando by making vehicles follow the mobility model. We feed the traces to network simulators to study the routing behavior. Simulation results show the performance and effectiveness of our modified and proposed routing protocols for VANET scenarios.

TOPO: Routing in Large Scale Vehicular Networks

A vehicular ad hoc network (VANET) is a high mobility wireless ad hoc network that is targeted to support vehicular safety, traffic monitoring, and other commercial applications. Routing in large scale VANET is an important issue, because road complexity and traffic variety may bring many potential problems that existing routing protocol can not address. In this paper, we introduce a two-phase routing protocol (TOPO) that incorporates map information in routing. The proposed protocol defines an overlay graph with roads of high vehicular density and forwards packet along the pre-calculated path in the overlay. We argue that the proposed TOPO can serve as a framework integrating existing VANET routing protocols. In particular, we adopt modified AODV and GPSR in the access (residential area) to send packets to overlay, while greedy forwarding is used in overlay. We also consider the data diversity in VANETs and design TOPO as an ITS friendly protocol. To validate our design philosophy and the routing protocol, we use real world road layouts in Orlando, and generate vehicular mobility traces following some mobility models. We feed the traces to network simulator and study the routing behavior. Simulation results show the performance and effectiveness of our proposed routing protocols for large scale VANET scenarios.

Cooperation in Wireless Networks with Unreliable Channels

In a distributed wireless system, multiple network nodes behave cooperatively towards a common goal. An important challenge in such a scenario is to attain mutual cooperation. This paper provides a non-cooperative game theoretic solution to enforce cooperation in wireless networks in the presence of channel noise. We focus on one-hop information exchange and model the packet forwarding process as a hidden action game with imperfect private monitoring. We propose a state machine based strategy to reach Nash Equilibrium. The equilibrium is proved to be a sequential one with carefully designed system parameters. Furthermore, we extend our discussion to a general wireless network scenario by considering how cooperation can prevail over collusion using evolutionary game theory. The simulation results are provided to back our analysis. In particular, network throughput performance is measured with respect to parameters like channel loss probability, route hop count, and mobility. Results suggest that the performance due to our proposed strategy is in close agreement with that of unconditionally cooperative nodes. Simulation results also reveal how the convergence of cooperation enforcement is affected by initial population share and channel unreliability.

Collaborative jamming and collaborative defense in Cognitive Radio Networks

Cognitive Radio Network (CRN) is one of the prominent communication technologies that is touted to drive the next generations of digital communications. In this paper, we address the vulnerabilities in such networks and analyze a common form of the Denial-of-Service attack, i.e., collaborative jamming. In particular, we model and analyze the channel availability when different jamming and defending schemes are employed by the attackers and legitimate users. Cooperative defense strategy is proposed to exploit the temporal and spatial diversity for the legitimate secondary users. Illustrative results show how to improve the resiliency in CRN against jamming attacks.

Enforcing cooperation in ad hoc networks with unreliable channel

An inherent assumption for packet forwarding in ad hoc networks is that the nodes will cooperate i.e., nodes can rely in each other. Thus, it is extremely important that cooperation is induced and achieved in the network. In this paper, we use game theory to analyze the necessary and sufficient conditions to enforce cooperation enforced, especially when a node cannot perfectly monitor other nodespsila behaviors. We analyze a credit exchange method under a general unreliable channel and show that the packet forwarding probability can be adjusted through proper design of incentives, which in turn can be used to attain the desired Nash Equilibrium. We extend our discussion to repeated games and take several well-known strategy profiles and derive the conditions under which the cooperation can lead to a subgame perfect Nash equilibrium. In particular, we show how the unreliable channel can affect the conditions and how a reputation based strategy leads to subgame perfection even under imperfect monitoring. We further investigate collusion resistance and cooperation coalition formation using evolutionary game theory. Mathematical proofs show the existence of an upper bound on the population share of the non-cooperative nodes for an evolutionarily non-stable strategy that enforces full cooperation. This bound is shown to depend on the nodespsila belief on the continuity of the game.

A game theoretic approach to detect and co-exist with malicious nodes in wireless networks

Identification and isolation of malicious nodes in a distributed system is a challenging problem. This problem is further aggravated in a wireless network because the unreliable channel hides the actions of each node from one another. Therefore, a regular node can only construct a belief about a malicious node through monitoring and observation. In this paper, we use game theory to study the interactions between regular and malicious nodes in a wireless network. We model the malicious node detection process as a Bayesian game with imperfect information and show that a mixed strategy perfect Bayesian Nash Equilibrium (also a sequential equilibrium) is attainable. While the equilibrium in the detection game ensures the identification of the malicious nodes, we argue that it might not be profitable to isolate the malicious nodes upon detection. As a matter of fact, malicious nodes can co-exist with regular nodes as long as the destruction they bring is less than the contribution they make. To show how we can utilize the malicious nodes, a post-detection game between the malicious and regular nodes is formalized. Solution to this game shows the existence of a subgame perfect Nash Equilibrium and reveals the conditions that are necessary to achieve the equilibrium. Further, we show how a malicious node can construct a belief about the belief held by a regular node. By employing the belief about the belief system, a Markov Perfect Bayes-Nash Equilibrium is reached and the equilibrium postpones the detection of the malicious node. Simulation results and their discussions are provided to illustrate the properties of the derived equilibria. The integration of the detection game and the post-detection is also studied and it is shown that the former one can transit into the latter one when the malicious node actively adjusts its strategies.

Attacker Detection Game in Wireless Networks with Channel Uncertainty

Identification and isolation of attackers in a distributed system is a challenging problem. This problem is even more aggravated in a wireless network because the unreliable channel makes the actions of the users (nodes) hidden from each other. Therefore, legitimate users can only construct a belief about a potential attacker through monitoring and observation. In this paper, we use game theory to study the interactions between regular and attacker nodes in a wireless network. We model the attacker node detection process as a Bayesian game with imperfect information and show that a mixed strategy perfect Bayesian Nash Equilibrium is attainable. Further, we show how an attacker node can construct a nested belief system to predict the belief held by a regular node. By employing the nested belief system, a Markov Perfect Bayes-Nash Equilibrium is reached and the equilibrium postpones the detection of the attacker node. Simulation results and their discussions are provided to illustrate the properties of the derived equilibria.

TCP Throughput for Vehicle-to-Vehicle Communications

It is well established that the relative movement of vehicles significantly affects the performance of the networking protocols in vehicle-to-vehicle communication. As TCP is the widely used end-to-end transport protocol, it is interesting to study its performance in such a highly mobile environment. In this paper, we consider a uni-directional motion of vehicles the velocities of which are gamma distributed. We present an analytical framework that forms the vehicle-to-vehicle network. With the help of a modified Bessel function of the second kind, we evaluate the cumulative distribution function of inter-vehicle distance. We also calculate the probability for catch-up and the expected time for it. The effect of round trip time and retransmission rate are studied which are then used to calculate the TCP throughput. Numerical results are presented that show high traffic density and diversity in velocity of the vehicles increase TCP throughput in a vehicle-to-vehicle network