Appearing in 1st IEEE International Workshop on Sensor Net Protocols and Applications (SNPA). Anchorage, Alaska, USA. May 11, 2003. RMST: Reliable Data Transport in Sensor Networks Fred Stann, John Heidemann Abstract – Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi- Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. Second, these energy constraints, plus relatively low wireless bandwidths, make in-network processing both feasible and desirable [3]. Third, because nodes in sensor networks are usually collaborating towards a common task, rather than representing independent users, optimization of the shared network focuses on throughput rather than fairness. Finally, because sensor networks are often deployed by a single organization with inexpensive hardware, there is less need for interoperability with existing standards. For all of these reasons, sensor networks provide an environment that encourages rethinking the structure of traditional communications protocols. The main contribution is an evaluation of the placement of reliability for data transport at different levels of the protocol stack. We consider implementing reliability in the MAC, transport layer, application, and combinations of these. We conclude that reliability is important at the MAC layer and the transport layer. MAC-level reliability is important not just to provide hop-by-hop error recovery for the transport layer, but also because it is needed for route discovery and maintenance. (This conclusion differs from previous studies in reliability for sensor nets that did not simulate routing. [4]) Second, we have developed RMST (Reliable Multi-Segment Transport), a new transport layer, in order to understand the role of in- network processing for reliable data transfer. RMST benefits from diffusion routing, adding minimal additional control traffic. RMST guarantees delivery, even when multiple hops exhibit very high error rates. 1 Introduction Wireless sensor networks provide an economical, fully distributed, sensing and computing solution for environments where conventional networks are impractical. This paper explores the design decisions related to providing reliable data transport in sensor nets. The reliable data transport problem in sensor nets is multi-faceted. The emphasis on energy conservation in sensor nets implies that poor paths should not be artificially bolstered via mechanisms such as MAC layer ARQ during route discovery and path selection [1]. Path maintenance, on the other hand, benefits from well- engineered recovery either at the MAC layer or the transport layer, or both. Recovery should not be costly however, since many applications in sensor nets are impervious to occasional packet loss, relying on the regular delivery of coarse-grained event descriptions. Other applications require loss detection and repair. These aspects of reliable data transport include the provision of guaranteed delivery and fragmentation/ reassembly of data entities larger than the network MTU. Sensor networks have different constraints than traditional wired nets. First, energy constraints are paramount in sensor networks since nodes can often not be recharged, so any wasted energy shortens their useful lifetime [2]. This work was supported by DARPA under grant DABT63-99-1-0011 as part of the SCAADS project, and was also made possible in part due to support from Intel Corporation and Xerox Corporation. Fred Stann and John Heidemann are with USC/Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA, USA E-mail: fstann@usc.edu, johnh@isi.edu. 2 Architectural Choices There are a number of key areas to consider when engineering reliability for sensor nets. Many current sensor networks exhibit high loss rates compared to wired networks (2% to 30% to immediate neighbors)[1,5,6]. While error detection and correction at the physical layer are important, approaches at the MAC layer and higher adapt well to the very wide range of loss rates seen in sensor networks and are the focus of this paper. MAC layer protocols can ameliorate PHY layer unreliability, and transport layers can guarantee delivery. An important question for this paper is the trade off between implementation of reliability at the MAC layer (i.e. hop to hop) vs. the Transport layer, which has traditionally been concerned with end-to-end reliability. Because sensor net applications are distributed, we also considered implementing reliability at the application layer. Our goal is to minimize the cost of repair in terms of transmission.

RMST: Reliable Data Transport in Sensor Networks

With the rapid development of the Intelligent Transportation System (ITS), vehicular communication networks have been widely studied in recent years. Dedicated Short Range Communication (DSRC) can provide efficient real-time information exchange among vehicles without the need of pervasive roadside communication infrastructure. Although mobile cellular networks are capable of providing wide coverage for vehicular users, the requirements of services that require stringent real-time safety cannot always be guaranteed by cellular networks. Therefore, the Heterogeneous Vehicular NETwork (HetVNET), which integrates cellular networks with DSRC, is a potential solution for meeting the communication requirements of the ITS. Although there are a plethora of reported studies on either DSRC or cellular networks, joint research of these two areas is still at its infancy. This paper provides a comprehensive survey on recent wireless networks techniques applied to HetVNETs. Firstly, the requirements and use cases of safety and non-safety services are summarized and compared. Consequently, a HetVNET framework that utilizes a variety of wireless networking techniques is presented, followed by the descriptions of various applications for some typical scenarios. Building such HetVNETs requires a deep understanding of heterogeneity and its associated challenges. Thus, major challenges and solutions that are related to both the Medium Access Control (MAC) and network layers in HetVNETs are studied and discussed in detail. Finally, we outline open issues that help to identify new research directions in HetVNETs.

Heterogeneous Vehicular Networking: A Survey on Architecture, Challenges, and Solutions

As a powerful tool, the vehicular network has been built to connect human communication and transportation around the world for many years to come. However, with the rapid growth of vehicles, the vehicular network becomes heterogeneous, dynamic, and large scaled, which makes it difficult to meet the strict requirements, such as ultralow latency, high reliability, high security, and massive connections of the next-generation (6G) network. Recently, machine learning (ML) has emerged as a powerful artificial intelligence (AI) technique to make both the vehicle and wireless communication highly efficient and adaptable. Naturally, employing ML into vehicular communication and network becomes a hot topic and is being widely studied in both academia and industry, paving the way for the future intelligentization in 6G vehicular networks. In this article, we provide a survey on various ML techniques applied to communication, networking, and security parts in vehicular networks and envision the ways of enabling AI toward a future 6G vehicular network, including the evolution of intelligent radio (IR), network intelligentization, and self-learning with proactive exploration.

Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches

Integrating the various embedded devices and systems in our environment enables an Internet of Things (IoT) for a smart city. The IoT will generate tremendous amount of data that can be leveraged for safety, efficiency, and infotainment applications and services for city residents. The management of this voluminous data through its lifecycle is fundamental to the realization of smart cities. Therefore, in contrast to existing surveys on smart cities we provide a data-centric perspective, describing the fundamental data management techniques employed to ensure consistency, interoperability, granularity, and reusability of the data generated by the underlying IoT for smart cities. Essentially, the data lifecycle in a smart city is dependent on tightly coupled data management with cross-cutting layers of data security and privacy, and supporting infrastructure. Therefore, we further identify techniques employed for data security and privacy, and discuss the networking and computing technologies that enable smart cities. We highlight the achievements in realizing various aspects of smart cities, present the lessons learned, and identify limitations and research challenges.

Smart Cities: A Survey on Data Management, Security, and Enabling Technologies

VANETs have emerged as an exciting research and application area. Increasingly vehicles are being equipped with embedded sensors, processing and wireless communication capabilities. This has opened a myriad of possibilities for powerful and potential life-changing applications on safety, efficiency, comfort, public collaboration and participation, while they are on the road. Although, considered as a special case of a Mobile Ad Hoc Network, the high but constrained mobility of vehicles bring new challenges to data communication and application design in VANETs. This is due to their highly dynamic and intermittent connected topology and different application's QoS requirements. In this work, we survey VANETs focusing on their communication and application challenges. In particular, we discuss the protocol stack of this type of network, and provide a qualitative comparison between most common protocols in the literature. We then present a detailed discussion of different categories of VANET applications. Finally, we discuss open research problems to encourage the design of new VANET solutions.

https://hal.archives-ouvertes.fr/hal-01369972/document

Data communication in VANETs

Multihop wireless broadcast is an important component in vehicular networks. Many applications are built on broadcast communications, so efficient routing methods are critical for their success. Here, we develop the Distribution-Adaptive Distance with Channel Quality (DADCQ) protocol to address this need and show that it performs well compared to several existing multihop broadcast proposals. The DADCQ protocol utilizes the distance method to select forwarding nodes. The performance of this method depends heavily on the value of the decision threshold, but it is difficult to choose a value that results in good performance across all scenarios. Node density, spatial distribution pattern, and wireless channel quality all affect the optimal value. Broadcast protocols tailored to vehicular networking must be adaptive to variation in these factors. In this work, we address this design challenge by creating a decision threshold function that is simultaneously adaptive to the number of neighbors, the node clustering factor, and the Rician fading parameter. To calculate the clustering factor, we propose using the quadrat method of spatial analysis. The resulting DADCQ protocol is then verified with JiST/SWANS and shown to achieve high reachability and low bandwidth consumption in urban and highway scenarios with varying node density and fading intensity.

Spatial Distribution and Channel Quality Adaptive Protocol for Multihop Wireless Broadcast Routing in VANET

Vehicular Ad-hoc NETworks (VANETs) are an emerging important type of wireless ad-hoc network. Unlike many other types of MANETs, VANET applications such as traffic data dissemination are inherently broadcast oriented and require communication protocols to be anonymous and scalable. Simple broadcast flooding satisfies these requirements, but its performance is highly dependent on network density and may lead to the broadcast storm problem.

This work is the first we are aware of to propose stochastic broadcast as a solution for VANET. Stochastic broadcast instructs nodes to rebroadcast messages according to a retransmit probability. Such a scheme is private since node identification is unnecessary, however it has an undesirable dependency on vehicle density in the same manner as simple flooding. To solve this problem, we demonstrate the link between the mathematical science of continuum percolation and stochastic broadcast. Specifically, that the critical percolation threshold in continuum percolation (≈ 4.5 expected neighbors) translates to the wireless broadcast context. Then we show that nodes can tune the performance of the broadcast system to efficient levels by adjusting the retransmit probability so the apparent density of the network approaches the critical threshold.

Stochastic Broadcast for VANET

Multi-hop broadcast is an important component in ad-hoc wireless networks. Some vehicular network (VANET) applications in particular use broadcast communications extensively. We propose using the distance-to-mean method to facilitate these applications. The performance of this method depends heavily on the value of the decision threshold, and it is difficult to choose a value for that threshold that results in good performance across a wide range of network scenarios. Node density, spatial distribution pattern, and wireless channel conditions all affect the optimal statistical threshold value. VANETs exhibit wide ranges of these factors, so protocols designed to support these applications must be adaptive to those variations. In this work we address this design challenge by using black-box optimization algorithms based on machine learning techniques such as genetic algorithms and particle swarm optimization to automatically discover a decision threshold value for the distance-to-mean method that is simultaneously adaptive to node density, node distribution pattern, and channel quality. The resulting decision surface is a function of the number of neighbors N, the quadrat statistic Q, and the Rician fading parameter K. The result is the Statistical Location-Assisted Broadcast (SLAB) protocol. Evaluations using JiST/SWANS show SLAB achieves high reachability and efficient bandwidth consumption in both urban and highway scenarios with varying node density.

Applying machine learning to the design of multi-hop broadcast protocols for VANET

Broadcast is a critical component in ad-hoc wireless networks. This paper examines the effects that channel unreliability have on the performance of broadcasting protocols. We show that the distance method of statistical broadcast performs poorly under adverse channel conditions. We then describe how to design a version of the distance method that is tolerant of transmission errors by adjusting the statistical variable threshold according to the channel conditions. The resulting protocol is then compared with the Double Covered Broadcast (DCB), a topological protocol designed to handle similar circumstances. The modified distance method protocol is shown to give similar reachability characteristics to DCB while using far less transmissions.

Statistical Broadcast Protocol Design for Unreliable Channels in Wireless Ad-Hoc Networks

Wireless sensors are promising and revolutionary technology. The sensor devices are typically deployed in large number to form a communication network for monitoring the physical environment. These devices are battery powered and the lifetime of the device is dependent on the battery's life. Once the battery's energy is depleted, the node is considered dead and is no longer part of the network. Recharging the sensors' batteries is not feasible, and in some cases, is completely impossible. Due to their severe energy constraints and redundancy in sensed data, hierarchal architectures are usually suggested for these networks. These architectures have proven effective in extending the network life several folds. The LEACH network routing protocol is the first protocol to use clustering for energy conservation in Wireless Sensor Networks. LEACH designers observe that there is an ideal percentage of nodes that need to be cluster heads to achieve optimal energy performance. For their work and performance analysis they selected 5% as the number of cluster heads in the netwok. The majority of routing protocols for WSNs follow LEACH and use clustering for energy performance optimization. Most of these protocols have taken the 5% percentage of cluster head as their ideal working setting, without independently qualifying this assumption. In this work, we use simulation modeling to investigate the dependency of this cluster head percentage on the network node density. Our results show that this percentage is not universal for all network settings, and is indeed dependent on the density. These findings will add to the challenging task of WSNs hierarchical networking protocols design.

Michael Slavik

Papers

Spatial Distribution and Channel Quality Adaptive Protocol for Multihop Wireless Broadcast Routing in VANET

Stochastic Broadcast for VANET

Applying machine learning to the design of multi-hop broadcast protocols for VANET

Statistical Broadcast Protocol Design for Unreliable Channels in Wireless Ad-Hoc Networks

Investigation of the effects of network density on the optimal number of clusters in hierarchical Wireless Sensor Networks (WSNs)