none

Doppler effects on vehicular communication have been theoretically modeled by many researchers. However, very limited experimental studies have been conducted to investigate the impact of Doppler shift on the vehicle-to-vehicle (V2V) communication range and reliability with high speed mobility. The current work-in-progress research aims to quantify the impact of Doppler effects on V2V communication reliability, range, and reachability using singlehop Dedicated Short Range communications (DSRC) between two opposite traffic. We conducted our experiments by mounting the after-market DSRC on-board units on the dashboard of two vehicles that cross each other from opposite directions with constant relative speeds on a real interstate freeway. Our preliminary results indicate that the communication time and range drop to approximately 70% and 40% after the two vehicles cross and start moving away from each other with the average relative speeds of 110 and 140 mph, respectively. Similarly, the packet delivery ratio is also drastically reduced after the vehicles start moving away from each other. Apparently, these results indicate that there might be a strong effect of Doppler phenomena on the transmission range, packet delivery rate and the duration of the communication.

Mobile Ad hoc Networks (MANETs) are wireless networks, which consist of a collection of mobile nodes with no fixed infrastructure, where each node acts as a router that participates in forwarding data packets. They are a new paradigm of wireless communications for mobile hosts that are resource-constrained with only limited energy, computing power and memory. Previous studies on MANETs concentrated more on energy conservation in an idealistic environment without taking into consideration, the effects of realistic mobility, interference and fading. The definition of realistic mobility models is one of the most critical and, at the same time, difficult aspects of the simulations of networks designed for real mobile ad hoc environments. The reason for this is that most scenarios for which ad hoc networks are used have features such as dynamicity and extreme uncertainties. Thus use of real life measurements is currently almost impossible and most certainly expensive. Hence the commonly used alternative is to simulate the movement patterns and hence the reproduction of movement traces quite similar to human mobility behavior is extremely important. The synthetic models used for movement pattern generation should reflect the movement of the real mobile devices, which are usually carried by humans, so the movement of such devices is necessarily based on human decisions. Regularity is an important characteristic of human movement patterns. All simulated movement models are suspect because there is no means of accessing to what extent they map reality. However it is not difficult to see that random mobility models such as Random Walk, Random Waypoint (default model used in almost all network simulations), etc., generate movements that are most non-humanlike. Hence we need to focus on more realistic mobility models such as Gauss Markov, Manhattan Grid, Reference Point Group Mobility Model (RPGM), Column, Pursue and other Hybrid mobility models. These models capture certain mobility characteristics that emulate the realistic MANETs movement, such as temporal dependency, spatial dependency and geographic restriction. Also a Rayleigh/Ricean fading channel is introduced to obtain a realistic fading environment. The energy consumed by the data, MAC, ARP and RTR packets using IEEE 802.11 MAC protocol with the various mobility models in fading and non-fading channel conditions are obtained using ns-2 simulations and AWK programs. The realistic movement patterns are generated using three different mobility generators BonnMotion Mobility Generator, Toilers Code and Scengen Mobility Generator. This thesis work performs an in-depth study on th eeffects of realistic mobility and fading on energy consumption, packet delivery ratio and control overhead of MANETs.

The size of the IoT network is expanding due to advancements in the IoT field, leading to increased interest in the multi-sink mechanism. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a representative IoT protocol that focuses on the Low-Power and Lossy Networks. However, research on comparing multi-sink strategies within the RPL network is limited. Therefore, this project aims to compare three common strategies: multiple-DODAG in one instance, virtual root, and multiple-instance. Using these strategies, we design and implement RPL networks and conduct simulations in various scenarios. Five different topologies are utilized in the experiments, considering different packet loss rates. Performance evaluation of each strategy is conducted using the Cooja simulator and Contiki-NG system, with a focus on the number of RPL control packets, Packet Delivery Ratio (PDR), and energy consumption. The results indicate that both the virtual root and multiple-DODAG strategies perform well with low packet loss, while the virtual root strategy outperforms the multiple-DODAG strategy with high packet loss. Additionally, the virtual root strategy incurs slightly higher energy costs than the multiple-DODAG strategy. Furthermore, the multiple-instance strategy demonstrates poor performance in most scenarios, except for the packet delivery ratio under high packet loss conditions. Besides the analysis, potential areas for future research on the RPL’s multi-sink mechanism are finally identified. / Storleken på IoT-nätverket expanderar på grund av framsteg inom IoT-området, vilket leder till ökat intresse för multi-sink-mekanismen. IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) är ett representativt IoT-protokoll som fokuserar på Nät med låg effekt och förluster. Forskningen om jämförelse av multi-sink-strategier inom RPL-nätverket är dock begränsad. Därför syftar detta projekt till att jämföra tre vanliga strategier: multiple - DODAG i en instans, virtuell rot och multi-instans. Med hjälp av dessa strategier designar och implementerar vi RPL-nätverk och genomför simuleringar i olika scenarier. Fem olika topologier används i experimenten, med olika packet loss rate. Prestationsutvärdering av varje strategi utförs med hjälp av Cooja-simulatorn och Contiki-NG-systemet, med fokus på antalet RPL control packets, Packet Delivery Ratio (PDR) och energiförbrukning. Resultaten indikerar att både virtuell rot och multiple-DODAG strategier fungerar bra vid låg datapaketförlust, medan den virtuella rotstrategin överträffar multiple-DODAG strategin vid hög datapaketförlust. Dessutom medför den virtuella rotstrategin något högre energikostnader än flera DODAG-strategin. Dessutom visar multi-instans-strategin dålig prestanda i de flesta scenarier, förutom när det gäller datapaketleveransförhållandet under höga datapaketförlustförhållanden. Utöver analysen identifieras slutligen potentiella områden för framtida forskning om RPL-protokollets multi-sink-mekanism.

由於VANET上的行動節點移動速度快，加上受到道路及交通號制的限制，導致網路拓樸快速改變，容易造成網路斷訊，影響資料封包在網路上的傳送效能。在傳統的MANET上有許多用來傳送資料封包的路由機制，並不直接適用在VANET上。隨著Global Position System (GPS)的普及，越來越多的車輛都具備GPS，用以輔助行車定位之用。在本研究中我們將透過GPS取得車輛的地理資訊，提出一個適用於VANET中以車行方向為基礎的貪婪路由演算法(MDBG)。 本論文目的在強化VANET網路上資料封包的路由選擇策略。所提出的路由機制將會透過hello message來取得相鄰車輛的位置和車行方向，並利用目標要求(DREQ)、目標回應(DREP)來獲得目標車輛的資訊。進而運用車輛的車行方向，選擇適當的相鄰車輛找出一條穩定的路由路徑。當來源車輛和目標車輛的車行方向相同時，AODV能有不錯的效能表現。而我們的路由演算法(MDBG)將強化當來源車輛和目標車輛的車行方向相反，並且逐漸遠離時的效能表現。實驗模擬的結果顯示MDBG在封包到達率、吞吐量和平均端對端延遲上較之於AODV及DSR演算法有更優異的表現。 / Packets transmission over VANET is intermittent due to rapid change of network topology. This comes from both high mobility of mobile nodes and road limitation. Intermittent transmission causes inefficient packet delivery. Those routing protocols applicable to MANET might not be suitable for VANET. On the other hand, Global Position System (GPS) is becoming prevalent in assisting positioning for vehicles. In this research, we develop a Moving Direction Based Greedy (MDBG) routing algorithm for VANET. MDBG algorithm is based on the geographical information collected by GPS. The objective of the thesis is to enhance routing decision in packet delivery. The "hello message" is used to retrieve the locations and moving directions of neighboring vehicles. Destination REQuest (DREQ) and Destination REPly (DREP) messages are used to retrieve target vehicle information. The source vehicle will thus use these information together with its own moving direction information to establish a stable routing path by selecting appropriate neighboring vehicles. AODV algorithm is proved to have good performance as both the source vehicle and target vehicle have the same moving direction. MDBG algorithm is proposed to leverage the problem as source vehicle and target vehicle move far apart in opposite directions. Simulation results show that MDBG outperforms both AODV and DSR in packet arrival rate, throughput and average end-to-end delay.

Recent advances in VLSI technology, and wireless communication have enabled the development of tiny, low-cost sensor nodes that communicate over short distances. These sensor nodes, which consist of sensing, data processing, and wireless communication capabilities, suggest the idea of sensor networks based on collaborative effort of a large number of sensor nodes. Sensor networks hold the promise for numerous applications such as intrusion detection, weather monitoring, security and tactical surveillance, distributed computing, and disaster management. Several new protocols and algorithms have been proposed in the recent past in order to realize these applications. In this thesis, we consider the problem of routing in Wireless Sensor Networks (WSNs). Routing is a challenging problem in WSNs due to the inherent characteristics which distinguish these networks from the others. Several routing algorithms have been proposed for WSNs, each considering a specific network performance objective such as long network lifetime (ChangandTassiulas,2004), end-to-end delay guarantees (T.Heetal,2003), and data fusion (RazvanCristescuetal,2005) etc. In this thesis, we utilize the Potential-based Routing Paradigm to develop routing algorithms for different performance objectives of interest in WSNs. The basic idea behind the proposed approach is to assign a scalar called the potential to every sensor node in the network. Data is then forwarded to the neighbor with highest potential. Potentials cause the data to flow along certain paths. By defining potential fields appropriately, one can cause data to flow along preferred paths, so that the given performance objective is achieved. We have demonstrated the usefulness of this approach by considering three performance objectives, and defining potentials appropriately in each case. The performance objectives that we have considered are (i) maximizing the time to network partition, (ii) maximizing the packet delivery ratio, and (iii) Data fusion. In an operational sensor network, sensor nodes’ energy levels gradually deplete, leading eventually to network partition. A natural objective is to route packets in such a way that the time to network partition is maximized. We have developed a potential function for this objective. We analyzed simple network cases and used the insight to develop a potential function applicable to any network. Simulation results showed that considerable improvements in time to network partition can be obtained compared to popular approaches such as maximum lifetime routing, and shortest hop count routing. In the next step, we designed a potential function that leads to routes with high packet delivery ratios. We proposed a “channel-state aware” potential definition for a simple 2-relay network and performed a Markov-chain based analysis to obtain the packet delivery ratio. Considerable improvement was observed compared to a channel-state-oblivious policy. This motivated us to define a channel-state-dependent potential function for a general network. Simulation results showed that for a relatively slowly changing wireless network, our approach can provide up to 20% better performance than the commonly-used shortest-hop-count routing. Finally, we considered the problem of correlated data gathering in sensor networks. The routing approach followed in literature is to construct a spanning tree rooted at the sink. Every node in the tree aggregates its data with the data from its children in order to reduce the number of transmitted bits. Due to this fact, the total energy cost of the data collection task is a function of the underlying tree structure. Noting that potential based routing schemes also result in a tree structure, we present a potential definition that results in the minimum energy cost tree under some special conditions. Specifically, we consider a scenario in which sensor nodes’ measurements are quantized to K values. The task at the sink is to construct a histogram of measurements of all sensor nodes. Sensor nodes do not directly send their measurements to sink. Instead, they construct a temporary histogram using the data from its children and forward it to its parent node in the tree. We present a potential definition that results in the minimum energy cost tree under some conditions on sensor nodes’ measurements. We include both the transmission energy cost as well as the energy cost associated with the aggregation process.

The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.