In recent years, significant advances have been achieved in communication networks and electric power systems. Communication networks are developed to provide services within not only well-connected network environments such as wireless local area networks, but also challenged network environments where continuous end-to-end connections can hardly be established between information sources and destinations. Delay tolerant network (DTN) is proposed to achieve this objective by utilizing a store-carry-and-forward routing scheme. However, as the network connections in DTNs are intermittent in nature, the management of network resources such as communication bandwidth and buffer storage becomes a challenging issue. On the other hand, the smart grid is to explore information and communication technologies in electric power grids to achieve electricity delivery in a more efficient and reliable way. A high penetration level of electric vehicles and renewable power generation is expected in the future smart grid. However, the randomness of electric vehicle mobility and the intermittency of renewable power generation bring new challenges to the resources management in the smart grid, such as electric power, energy storage, and communication bandwidth management. This thesis consists of two parts. In part I, we focus on the resource management in DTNs. Specifically, we investigate data dissemination and on-demand data delivery which are two of the major data services in DTNs. Two kinds of mobile nodes are considered for the two types of services which correspond to the pedestrians and high-speed train passengers, respectively. For pedestrian nodes, the roadside wireless local area networks are used as an auxiliary communication infrastructure for data service delivery. We consider a cooperative data dissemination approach with a packet pre-downloading mechanism and propose a double-loop receiver-initiated medium access control scheme to resolve the channel contention among multiple direct/relay links and exploit the predictable traffic characteristics as a result of packet pre-downloading. For high-speed train nodes, we investigate on-demand data service delivery via a cellular/infostation integrated network. The optimal resource allocation problem is formulated by taking account of the intermittent network connectivity and multi-service demands. In order to achieve efficient resource allocation with low computational complexity, the original problem is transformed into a single-machine preemptive scheduling problem and an online resource allocation algorithm is proposed. If the link from the backbone network to an infostation is a bottleneck, a service pre-downloading algorithm is also proposed to facilitate the resource allocation. In part II, we focus on resource management in the smart grid. We first investigate the optimal energy delivery for plug-in hybrid electric vehicles via vehicle-to-grid systems. A dynamic programming formulation is established by considering the bidirectional energy flow, non-stationary energy demand, battery characteristics, and time-of-use electricity price. We prove the optimality of a state-dependent double-threshold policy based on the stochastic inventory theory. A modified backward iteration algorithm is devised for practical applications, where an exponentially weighted moving average algorithm is used to estimate the statistics of vehicle mobility and energy demand. Then, we propose a decentralized economic dispatch approach for microgrids such that the optimal decision on power generation is made by each distributed generation unit locally via multiagent coordination. To avoid a slow convergence speed of multiagent coordination, we propose a heterogeneous wireless network architecture for microgrids. Two multiagent coordination schemes are proposed for the single-stage and hierarchical operation modes, respectively. The optimal number of activated cellular communication devices is obtained based on the tradeoff between communication and generation costs.

In recent years, significant advances have been achieved in communication networks and electric power systems. Communication networks are developed to provide services within not only well-connected network environments such as wireless local area networks, but also challenged network environments where continuous end-to-end connections can hardly be established between information sources and destinations. Delay tolerant network (DTN) is proposed to achieve this objective by utilizing a store-carry-and-forward routing scheme. However, as the network connections in DTNs are intermittent in nature, the management of network resources such as communication bandwidth and buffer storage becomes a challenging issue. On the other hand, the smart grid is to explore information and communication technologies in electric power grids to achieve electricity delivery in a more efficient and reliable way. A high penetration level of electric vehicles and renewable power generation is expected in the future smart grid. However, the randomness of electric vehicle mobility and the intermittency of renewable power generation bring new challenges to the resources management in the smart grid, such as electric power, energy storage, and communication bandwidth management. This thesis consists of two parts. In part I, we focus on the resource management in DTNs. Specifically, we investigate data dissemination and on-demand data delivery which are two of the major data services in DTNs. Two kinds of mobile nodes are considered for the two types of services which correspond to the pedestrians and high-speed train passengers, respectively. For pedestrian nodes, the roadside wireless local area networks are used as an auxiliary communication infrastructure for data service delivery. We consider a cooperative data dissemination approach with a packet pre-downloading mechanism and propose a double-loop receiver-initiated medium access control scheme to resolve the channel contention among multiple direct/relay links and exploit the predictable traffic characteristics as a result of packet pre-downloading. For high-speed train nodes, we investigate on-demand data service delivery via a cellular/infostation integrated network. The optimal resource allocation problem is formulated by taking account of the intermittent network connectivity and multi-service demands. In order to achieve efficient resource allocation with low computational complexity, the original problem is transformed into a single-machine preemptive scheduling problem and an online resource allocation algorithm is proposed. If the link from the backbone network to an infostation is a bottleneck, a service pre-downloading algorithm is also proposed to facilitate the resource allocation. In part II, we focus on resource management in the smart grid. We first investigate the optimal energy delivery for plug-in hybrid electric vehicles via vehicle-to-grid systems. A dynamic programming formulation is established by considering the bidirectional energy flow, non-stationary energy demand, battery characteristics, and time-of-use electricity price. We prove the optimality of a state-dependent double-threshold policy based on the stochastic inventory theory. A modified backward iteration algorithm is devised for practical applications, where an exponentially weighted moving average algorithm is used to estimate the statistics of vehicle mobility and energy demand. Then, we propose a decentralized economic dispatch approach for microgrids such that the optimal decision on power generation is made by each distributed generation unit locally via multiagent coordination. To avoid a slow convergence speed of multiagent coordination, we propose a heterogeneous wireless network architecture for microgrids. Two multiagent coordination schemes are proposed for the single-stage and hierarchical operation modes, respectively. The optimal number of activated cellular communication devices is obtained based on the tradeoff between communication and generation costs.

Zugl.: Ilmenau, Techn. Univ., Diss., 2010

在耐延遲網路(Delay Tolerant Network)中，因節點之間的高移動性、連接的不確定性環境嚴苛限制，採用Store-And-Forward 訊息傳輸的模式提供一個可接受的網路表現。常見的路由協定可分為機會路由、基於預測的路由以及調度路由，然而這些路由協定使用在市區環境中，有些許不足的地方，因此我們提出適用在市區封包轉發策略。 我們提出的以公車亭為基礎之耐延遲車載網路封包轉發策略，是在市區環境中建立一個以公車亭為基礎的資料傳送架構，包含汽車、公車、公車站、公車轉運站四種節點。我們建立節點與節點相遇時資料傳送規則，例如汽車與汽車相遇、汽車與公車相遇、公車與公車站相遇、公車與公車轉運站相遇、公車轉運站與公車相遇、公車站與汽車相遇、汽車與目的地相遇時各自有不同的資料傳送判斷與限制。 實驗結果也證明所提出的演算法，除了可以有效地減少延遲傳送時間並提高訊息成功傳送率，及在各節點有限的緩衝區大小下，我們的封包轉發策略有著最突出的效能。 / In Delay Tolerant Networks (DTNs), there does not exist an end-to-end path due to intermittent connectivity and high node mobility. Messages are stored for a period of time at network nodes and are conveyed hop-by-hop to the destination. The current DTN routing protocols can be summarized into three categories: opportunistic, prediction-based and scheduling protocols. However, these routing protocols have some deficiencies and are not specifically focused on the urban areas. Based on the characteristics of urban areas, we proposed a kiosk based packet forwarding strategy for vehicular delay tolerant networks. We established the rules of data transmission when one node contacts other nodes. More specifically, Car-to-Car, Car-to-Bus, Bus-to-Bus stop, Bus-to-Bus transfer station, Bus transfer station-to-Bus, Bus stop-to-Car ,Car-to-Destination contacts, have different judgments and restrictions for data forwarding. The simulation results demonstrate that we proposed packet forwarding strategy would reduce the delivery delay, and improve the successful delivery rate. Especially with limited buffer and little overhead, our proposed strategy has the most prominent performance.

許多國家正面臨因嚴重的交通壅塞所帶來龐大的經濟損失，同樣在台灣也面臨相同問題，根本解決之道就是找出壅塞路段，並即時地告知車輛駕駛以迴避此路段。因此如何有效率地偵測出壅塞路段，是當前重要的議題。以往大多透過長期所累積的統計數據，針對各路段收集行駛於該路段所有車輛的平均速度，來獲得該路段的交通狀況，但卻無法立即反應即時路況。 因此我們提出以耐延遲車載網路方式，收集路況資訊與彙整旅途時程，透過具有全球定位系統(GPS)以及無線網路的車輛來進行路況交通資訊的收整與交換。再透過本研究所提出路況交通覺知路由協定(RTARP)，以One-Hop Controlled Flooding的傳輸方式在節點與節點相遇時進行路況資訊的傳送，進而交換節點彼此間各自所存放各路段的路況資訊。 模擬實驗結果證明我們所提出的路由協定在路況交通資訊交換中，有效地減少網路傳輸負載、提高訊息送達成功率以及路況交通資訊(RTI)正確率。 / Many countries are concerning about the huge economic losses caused by the critical traffic congestion. We have the same problem in Taiwan. The solutions lie in finding the road section with traffic congestion first and informing drivers to avoid that section. But how to detect the road section with traffic congestion effectively is the most important issue of this research. Conventionally, the real-time road traffic is mostly predicted by long-term accumulated statistics calculated by the collection of the average speed of cars on the same road section. But this way can’t provide the real-time road traffic immediately. Based on vehicles with GPS and the capability of WiFi, we proposed gathering road traffic information and consolidating travel time estimation using vehicular delay tolerant networks. We also proposed the Road Traffic Awareness Routing Protocol (RTARP) to exchange the road traffic information preserved individually by One-Hop Controlled Flooding during nodes’ encounter. The results of simulations prove the routing protocol we proposed can effectively reduce the transmission overhead, improve the delivery ratio and the accuracy of the road traffic information.

IEEE 802.11 PHY supports multiple transmission rates according to multiple different modulations and coding schemes. Each WiFi station selects its own transmission rate according to its own algorithm; in particular, the IEEE 802.11 standards do not specify the bit-rate selection method. Although many adaptive bit-rate selection algorithms have been proposed, there is limited research and evaluation on the performance of such algorithms for roadside networks, especially in cases with multi-vehicle roadside multi-vehicular WiFi networks. In this thesis we propose an opportunistic highest bit-rate algorithm, Opportunistic Highest Bit-Rate Multi-Vehicular WiFi Networks (OHBR-MVN), specifically for roadside multi-vehicular WiFi networks. Our proposal is based on three key characteristics of such networks: (1) vehicles will drive closer to, and eventually pass, the roadside WiFi station, experiencing a progressively better transmission environment; (2) the vast majority of data transmitted in single-vehicle drive-by downloading scenarios occurs at the maximum transmission rate; (3) vehicles that transmit at less than the maximum rate do so at the expense of those that could send more data at a higher transmission rate. We therefore believe that transmitting only at the highest possible bit-rate is the preferred algorithm for such networks. Further, this approach keeps the bit-rate selection extremely simple, avoiding the complexity and resulting problems of adaptive approaches. Through a series of experiments that compare the throughput of both fixed and adaptive bit-rate selection algorithms we show that our approach yields both higher throughput and better fairness characteristics, while being significantly simple, and thus more robust.

The delay tolerant networks (DTNs) is characterized by frequent disconnections and long delays of links among devices due to mobility, sparse deployment of devices, attacks, and noise, etc. Considerable research efforts have been devoted recently to DTNs enabling communications between network entities with intermittent connectivity. Unfortunately, mobile devices have limited energy capacity, and the fundamental problem is that traditional power-saving mechanisms are designed assuming well connected networks. Due to much larger inter-contact durations than contact durations, devices spend most of their life time in the neighbor discovery, and centralized power-saving strategies are difficult. Consequently, mobile devices consume a significant amount of energy in the neighbor discovery, rather than in infrequent data transfers. Therefore, distributed energy efficient neighbor discovery protocols for DTNs are essential to minimize the degradation of network connectivity and maximize the benefits from mobility. In this thesis, we develop sleep scheduling protocols in the medium access control (MAC) layer that are adaptive and distributed under different clock synchronization conditions: synchronous, asynchronous, and semi-asynchronous. In addition, we propose a distributed clock synchronization protocol to mitigate the clock synchronization problem in DTNs. Our research accomplishments are briefly outlined as follows: Firstly, we design an adaptive exponential beacon (AEB) protocol. By exploiting the trend of contact availability, beacon periods are independently adjusted by each device and optimized using the distribution of contact durations. The AEB protocol significantly reduces energy consumption while maintaining comparable packet delivery delay and delivery ratio. Secondly, we design two asynchronous clock based sleep scheduling (ACDS) protocols. Based on the fact that global clock synchronization is difficult to achieve in general, predetermined patterns of sleep schedules are constructed using hierarchical arrangements of cyclic difference sets such that devices independently selecting different duty cycle lengths are still guaranteed to have overlapping awake intervals with other devices within the communication range. Thirdly, we design a distributed semi-asynchronous sleep scheduling (DSA) protocol. Although the synchronization error is unavoidable, some level of clock accuracy may be possible for many practical scenarios. The sleep schedules are constructed to guarantee contacts among devices having loosely synchronized clocks, and parameters are optimized using the distribution of synchronization error. We also define conditions for which the proposed semi-asynchronous protocol outperforms existing asynchronous sleep scheduling protocols. Lastly, we design a distributed clock synchronization (DCS) protocol. The proposed protocol considers asynchronous and long delayed connections when exchanging relative clock information among nodes. As a result, smaller synchronization error achieved by the proposed protocol allows more accurate timing information and renders neighbor discovery more energy efficient. The designed protocols improve the lifetime of mobile devices in DTNs by means of energy efficient neighbor discoveries that reduce the energy waste caused by idle listening problems.

Mobile Delay Tolerant Networks (MDTNs) are wireless mobile networks in which a complete routing path between two nodes that wish to communicate cannot be guaranteed. A number of networking scenarios have been categorized as MDTNs, such as vehicular ad hoc networks, pocket switched networks, etc. The network asynchrony, coupled with the limited resources of mobile devices make message dissemination (also called routing) one of the fundamental challenges in MDTNs. In the literature, a large body of work has been done to deal with routing in MDTNs. However, most of the existing routing protocols are based on at least one of the following three assumptions: (1) all messages can be routed by relying on a single mobility property; (2) all messages can be routed using a single message allocation strategy; (3) users are willing to disclose their mobility information and relationships to others in order to improve the quality of the routing. We argue that the above three assumptions are not realistic because: (1) users can exhibit various social behaviors and consequently various mobility properties (e.g., they can have regular movements during week-days and exhibit non-predictable movements during week-ends); (2) some messages might need more or less copies to be delivered according to the localization of the source and the destination and to the urgency of the message; and (3) users mobility data can disclose sensitive information about the users. In this thesis, we relieve MDTN routing from the above three restrictive assumptions. Firstly, we propose an adaptive routing protocol for mobile delay tolerant networks. The proposed protocol can dynamically learn the social properties of nodes based on their mobility patterns, and exploit the most appropriate routing strategy each time an intermediate node is encountered. Simulations performed on real mobility traces show that our protocol achieves a better delivery ratio than existing state-of-the-art routing protocols that rely on a single mobility property. Secondly, we present a delay and cost balancing protocol for efficient routing in mobile delay tolerant networks. The presented protocol reasons on the remaining time-to-live of a message to dynamically allocate the minimum number of copies that are necessary to achieve a given delivery probability. Evaluation results show that the protocol can achieve a good balance between message delivery delay and delivery cost, compared with most of the existing routing protocols in the literature. Lastly, we propose an efficient privacy preserving prediction-based routing protocol for mobile delay tolerant networks. This protocol preserves the mobility patterns of a node from being disclosed by exploiting the mobility pattern of communities that node belongs to. Evaluation results demonstrate that this protocol can obtain comparable routing performance to prediction-based protocols while preserving the mobility pattern of nodes.

IEEE 802.11 PHY supports multiple transmission rates according to multiple different modulations and coding schemes. Each WiFi station selects its own transmission rate according to its own algorithm; in particular, the IEEE 802.11 standards do not specify the bit-rate selection method. Although many adaptive bit-rate selection algorithms have been proposed, there is limited research and evaluation on the performance of such algorithms for roadside networks, especially in cases with multi-vehicle roadside multi-vehicular WiFi networks. In this thesis we propose an opportunistic highest bit-rate algorithm, Opportunistic Highest Bit-Rate Multi-Vehicular WiFi Networks (OHBR-MVN), specifically for roadside multi-vehicular WiFi networks. Our proposal is based on three key characteristics of such networks: (1) vehicles will drive closer to, and eventually pass, the roadside WiFi station, experiencing a progressively better transmission environment; (2) the vast majority of data transmitted in single-vehicle drive-by downloading scenarios occurs at the maximum transmission rate; (3) vehicles that transmit at less than the maximum rate do so at the expense of those that could send more data at a higher transmission rate. We therefore believe that transmitting only at the highest possible bit-rate is the preferred algorithm for such networks. Further, this approach keeps the bit-rate selection extremely simple, avoiding the complexity and resulting problems of adaptive approaches. Through a series of experiments that compare the throughput of both fixed and adaptive bit-rate selection algorithms we show that our approach yields both higher throughput and better fairness characteristics, while being significantly simple, and thus more robust.

The delay tolerant networks (DTNs) is characterized by frequent disconnections and long delays of links among devices due to mobility, sparse deployment of devices, attacks, and noise, etc. Considerable research efforts have been devoted recently to DTNs enabling communications between network entities with intermittent connectivity. Unfortunately, mobile devices have limited energy capacity, and the fundamental problem is that traditional power-saving mechanisms are designed assuming well connected networks. Due to much larger inter-contact durations than contact durations, devices spend most of their life time in the neighbor discovery, and centralized power-saving strategies are difficult. Consequently, mobile devices consume a significant amount of energy in the neighbor discovery, rather than in infrequent data transfers. Therefore, distributed energy efficient neighbor discovery protocols for DTNs are essential to minimize the degradation of network connectivity and maximize the benefits from mobility. In this thesis, we develop sleep scheduling protocols in the medium access control (MAC) layer that are adaptive and distributed under different clock synchronization conditions: synchronous, asynchronous, and semi-asynchronous. In addition, we propose a distributed clock synchronization protocol to mitigate the clock synchronization problem in DTNs. Our research accomplishments are briefly outlined as follows: Firstly, we design an adaptive exponential beacon (AEB) protocol. By exploiting the trend of contact availability, beacon periods are independently adjusted by each device and optimized using the distribution of contact durations. The AEB protocol significantly reduces energy consumption while maintaining comparable packet delivery delay and delivery ratio. Secondly, we design two asynchronous clock based sleep scheduling (ACDS) protocols. Based on the fact that global clock synchronization is difficult to achieve in general, predetermined patterns of sleep schedules are constructed using hierarchical arrangements of cyclic difference sets such that devices independently selecting different duty cycle lengths are still guaranteed to have overlapping awake intervals with other devices within the communication range. Thirdly, we design a distributed semi-asynchronous sleep scheduling (DSA) protocol. Although the synchronization error is unavoidable, some level of clock accuracy may be possible for many practical scenarios. The sleep schedules are constructed to guarantee contacts among devices having loosely synchronized clocks, and parameters are optimized using the distribution of synchronization error. We also define conditions for which the proposed semi-asynchronous protocol outperforms existing asynchronous sleep scheduling protocols. Lastly, we design a distributed clock synchronization (DCS) protocol. The proposed protocol considers asynchronous and long delayed connections when exchanging relative clock information among nodes. As a result, smaller synchronization error achieved by the proposed protocol allows more accurate timing information and renders neighbor discovery more energy efficient. The designed protocols improve the lifetime of mobile devices in DTNs by means of energy efficient neighbor discoveries that reduce the energy waste caused by idle listening problems.