No Arabic abstract
In many scenarios, control information dissemination becomes a bottleneck, which limits the scalability and the performance of wireless networks. Such a problem is especially crucial in mobile ad hoc networks, dense networks, networks of vehicles and drones, sensor networks. In other words, this problem occurs in any scenario with frequent changes in topology or interference level on one side and with strong requirements on delay, reliability, power consumption, or capacity on the other side. If the control information changes partially, it may be worth sending only differential updates instead of messages containing full information to reduce overhead. However, such an approach needs accurate tuning of dissemination parameters, since it is necessary to guarantee information relevance in error-prone wireless networks. In the paper, we provide a deep study of two approaches for generating differential updates - namely, incremental and cumulative - and compare their efficiency. We show that the incremental approach allows significantly reducing the amount of generated control information compared to the cumulative one, while providing the same level of information relevance. We develop an analytical model for the incremental approach and propose an algorithm which allows tuning its parameters, depending on the number of nodes in the network, their mobility, and wireless channel quality. Using the developed analytical model, we show that the incremental approach is very useful for static dense network deployments and networks with low and medium mobility, since it allows us to significantly reduce the amount of control information compared to the classical full dump approach.
How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. In this paper, we start with analyzing characteristics of a taxi GPS dataset and then establishing the vehicular-to-infrastructure, vehicle-to-vehicle and the hybrid communication model, respectively. Moreover, we propose a clustering algorithm for station selection, a traffic allocation optimization model and an information source selection model based on the communication performances and complex network theory.
In wireless industrial networks, the information of time-sensitive control systems needs to be transmitted in an ultra-reliable and low-latency manner. This letter studies the resource allocation problem in finite blocklength transmission, in which the information freshness is measured as the age of information (AoI) whose maximal AoI is characterized using extreme value theory (EVT). The considered system design is to minimize the sensors transmit power and transmission blocklength subject to constraints on the maximal AoIs tail behavior. The studied problem is solved using Lyapunov stochastic optimization, and a dynamic reliability and age-aware policy for resource allocation and status updates is proposed. Simulation results validate the effectiveness of using EVT to characterize the maximal AoI. It is shown that sensors need to send larger-size data with longer transmission blocklength at lower transmit power. Moreover, the maximal AoIs tail decays faster at the expense of higher average information age.
Information dissemination applications (video, news, social media, etc.) with large number of receivers need to be efficient but also have limited loss tolerance. The new Information-Centric Networks (ICN) paradigm offers an alternative approach for reliably delivering data by naming content and exploiting data available at any intermediate point (e.g., caches). However, receivers are often heterogeneous, with widely varying receive rates. When using existing ICN congestion control mechanisms with in-sequence delivery, a particularly thorny problem of receivers going out-of-sync results in inefficiency and unfairness with heterogeneous receivers. We argue that separating reliability from congestion control leads to more scalable, efficient and fair data dissemination, and propose SAID, a Control Protocol for Scalable and Adaptive Information Dissemination in ICN. To maximize the amount of data transmitted at the first attempt, receivers request any next packet (ANP) of a flow instead of next-in-sequence packet, independent of the providers transmit rate. This allows providers to transmit at an application-efficient rate, without being limited by the slower receivers. SAID ensures reliable delivery to all receivers eventually, by cooperative repair, while preserving privacy without unduly trusting other receivers.
Wireless mesh networks are a promising technology for connecting sensors and actuators with high flexibility and low investment costs. In industrial applications, however, reliability is essential. Therefore, two time-slotted medium access methods, DSME and TSCH, were added to the IEEE 802.15.4 standard. They allow collision-free communication in multi-hop networks and provide channel hopping for mitigating external interferences. The slot schedule used in these networks is of high importance for the network performance. This paper supports the development of efficient schedules by providing an analytical model for the assessment of such schedules, focused on TSCH. A Markov chain model for the finite queue on every node is introduced that takes the slot distribution into account. The models of all nodes are interconnected to calculate network metrics such as packet delivery ratio, end-to-end delay and throughput. An evaluation compares the model with a simulation of the Orchestra schedule. The model is applied to Orchestra as well as to two simple distributed scheduling algorithms to demonstrate the importance of traffic-awareness for achieving high throughput.
Multicast is a central challenge for emerging multi-hop wireless architectures such as wireless mesh networks, because of its substantial cost in terms of bandwidth. In this report, we study one specific case of multicast: broadcasting, sending data from one source to all nodes, in a multi-hop wireless network. The broadcast we focus on is based on network coding, a promising avenue for reducing cost; previous work of ours showed that the performance of network coding with simple heuristics is asymptotically optimal: each transmission is beneficial to nearly every receiver. This is for homogenous and large networks of the plan. But for small, sparse or for inhomogeneous networks, some additional heuristics are required. This report proposes such additional new heuristics (for selecting rates) for broadcasting with network coding. Our heuristics are intended to use only simple local topology information. We detail the logic of the heuristics, and with experimental results, we illustrate the behavior of the heuristics, and demonstrate their excellent performance.