Cooperative perception significantly enhances the perception performance of connected autonomous vehicles. Instead of purely relying on local sensors with limited range, it enables multiple vehicles and roadside infrastructures to share sensor data to perceive the environment collaboratively. Through our study, we realize that the performance of cooperative perception systems is limited in real-world deployment due to (1) out-of-sync sensor data during data fusion and (2) inaccurate localization of occluded areas. To address these challenges, we develop RAO, an innovative, effective, and lightweight cooperative perception system that merges asynchronous sensor data from different vehicles through our novel designs of motion-compensated occupancy flow prediction and on-demand data sharing, improving both the accuracy and coverage of the perception system. Our extensive evaluation, including real-world and emulation-based experiments, demonstrates that RAO outperforms state-of-the-art solutions by more than 34% in perception coverage and by up to 14% in perception accuracy, especially when asynchronous sensor data is present. RAO consistently performs well across a wide variety of map topologies and driving scenarios. RAO incurs negligible additional latency (8.5 ms) and low data transmission overhead (10.9 KB per frame), making cooperative perception feasible.

This paper proposes Forwarding Game Routing Protocol (FGRP), which can be applied to any routing protocol in mobile ad hoc network (MANET) such as Ad Hoc On Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) routing protocols. A node enters the forwarding game upon receiving a flooding packet. In this game, nodes select one of the following mixed strategies: (1) forwarding and (2) not-forwarding. The strategy changes based on player's utility, which is a function of its availability, selected strategy and forwarding probability of other nodes. Each node tries to maximize its utility by selecting the appropriate strategy. Parameters such as residual energy level, channel congestion, number of packets in the node's queue, and the distance from the source of the flooding packet are included in the availability. Since the forwarding decision is made locally by every node, unlike clustering or hierarchical algorithms, there is no extra overhead involved. This paper presents the performance improvement results of FGRP integrated with AODV in network simulator NS-2. Simulation results show that integrating FGRP with AODV improves network performance metrics such as end-to-end delay per packet, and packet delivery ratio.

Although several routing protocols have been proposed that can be used in mobile ad hoc networks, there is very little formal analysis that considers the communication overhead or in other word routing overhead for these procedures. This paper provides a new mathematical framework for quantifying the overhead of reactive routing protocols such as dynamic source routing (DSR) and ad hoc on-demand distance vector routing (AODV) in wireless ad hoc networks with random location of the nodes. The analysis is compared with the simulations and found to match with the simulation results . The result of this study can be used to predict scalability properties of routing protocols.

In this paper, hierarchical dynamic source routing (HDSR) protocol is introduced. HDSR is derived from dynamic source routing (DSR) protocol. In HDSR, there are two states that a mobile node can be: mobile node (MN) and forwarding node (FN). Network nodes make distributed decisions on whether to forward or not to forward traffic for others. FN routes the packets and MN hosts the applications. FN selections are made using local information and nodes solely rely on "on demand" routing discovery and maintenance traffic to determine whether to act as MN or FN. Such provisions, significantly reduce number of control messages (route request and route reply) in compare to DSR. HDSR is implemented by a network simulator (network simulator-2 of University of California). It was shown via computer simulations that HDSR improves average network throughput and packet delivery ratio compared to regular DSR and provides energy efficiency.

In this paper, energy saving dynamic source routing (ESDSR) protocol is introduced to maximize the life-span of a mobile ad hoc network (MANET). Many theoretical studies show that energy consumption in MANET can be significantly reduced using energy-aware routing protocols compared to fixed-power minimum-hop routing protocols. Two approaches are broadly suggested for energy-aware routing protocols - transmission power control approach and load sharing approach. ESDSR integrates the advantages of those two approaches. In ESDSR, the routing decision is based on a load balancing approach. Once a routing decision is made, link by link transmit power adjustment per packet is done based on a transmit power control approach. We modified dynamic source routing (DSR) protocol to make it energy aware by a network simulator (network simulator-2 of University of California). The simulation results show that the proposed ESDSR can save energy up to 40% per packet and it can send 20 % more packets to destinations by spending the same battery power in compare to DSR.