mRPL+: A mobility management framework in RPL/6LoWPAN
Introduction
Most research in low-power wireless networks (LPWNs) assumes static nodes and networks with negligible topological changes, deriving mostly from variations in the surrounding environment, such as electromagnetic noise, physical conditions (temperature, humidity, pressure) and moving entities (people, vehicles, animals, furniture, objects). However, there is an increasing demand for new applications benefiting from or even imposing mobility support [1], [2], [3], [4]. The next generation Internet, known as Internet of Things (IoT), defines an advanced connectivity for all wireless devices. Supporting mobility in an Internet Protocol (IP)-based LPWN application is paramount as it enables integrating LPWNs with other wireless networks that support mobility.
The 5G technology is the next generation of mobile communication standards that will be operational by 2020 [5]. This technology is expected to support higher data rate, lower end-to-end latency, and achieve improved coverage with respect to 4G to handle most demanding IoT applications [6]. Mobile devices are the basic elements of critical IoT applications within 5G networks. A distributed mobility management is one of the requirements of these applications in order to provide better network connectivity [7].
The IEEE 802.15.4 is a standard protocol that is widely used in LPWNs. The Internet Engineering Task Force (IETF) specified some protocols and adaptation layers that allow Internet Protocol version 6 (IPv6) to run over the IEEE 802.15.4 link layer. The IPv6 over Low-power Wireless Personal Area Networks (6LoWPAN) working group [8] specified header compression and fragmentation for IPv6 over IEEE 802.15.4 [9]. The IETF Routing Over Low-power and Lossy networks (ROLL) working group standardized a routing protocol, referred to as RPL [10], which is the de-facto standard routing protocol for 6LoWPAN. These IP-based standards (6LoWPAN and RPL) are thus the fundamental communication building blocks for the IoT.
In higher power wireless networks, such as cellular networks, there is high demand from users when nodes are moving. However, these wireless networks are quite different in their design and capabilities, demanding for different mobility solutions, as they are based on the following features: i) backbone of wired base stations, ii) platforms with high-processing capability, iii) support of multiple radios (each node with multiple antennas), and (iv) hardware assisted location information by using Global Positioning System (GPS). Thus, the mobility management mechanisms are usually very accurate, yet complex. LPWNs lack a backbone of wired access points (APs). Moreover, wireless nodes have low-power, low-processing, low-energy and low-communication resources and are usually limited to a single radio, which prevents simultaneous transmission/reception. Links are usually short range, very dynamic and unreliable. Consequently, the design of a mobility management mechanism requires careful consideration, in order to be (i) light, in terms of overhead (number of control message exchange), ii) fast, in what concerns guaranteeing short network inaccessibility times upon mobility (during hand-off), and iii) reliable, so that packet delivery ratio remains unchanged upon nodes’ mobility.
Many LPWN applications within 5G network will impose stringent timing and reliability requirements for transmitting critical messages from source to destination, but providing Quality of Service (QoS) in low-power and mobile networks is a challenging issue. To exemplify this fact, in clinical monitoring, patients have embedded wireless sensing devices that must report data in real-time [11], [12]. In oil refineries, the vital signs of workers are collected continuously in order to monitor their health situation in dangerous environments [13].
A simple solution to support mobility in low-power networks is for mobile nodes to broadcast data to all neighbor nodes in their vicinity [14]. This broadcast approach leads to redundant information at neighboring nodes since more than one node is likely to receive the same packet. This implies that the fixed infrastructure has either to waste resources in forwarding the same information to the sink node, or to use a complex scheme, such as data aggregation [15] in order to eliminate duplicated packets.
Two main algorithms are identified in RPL and 6LoWPAN that partially cope with mobility. First, the periodic transmission of control packets, scheduled by the Trickle algorithm [16] can detect topological changes. During this process, RPL resumes a fast global routing update that causes a high overhead. Second, it resumes the Neighbor Discovery (ND – defined in RFC 4861 [17]) algorithm that assesses the neighbor reachability in a regular basis. Upon activating the Trickle and ND algorithms, RPL floods the entire network with beacons, leading to an increase in network overhead and energy waste. However, if these algorithms are activated very sparsely (long periods), which is the case in low traffic and static networks, the network may not be responsive enough. This will eventually increase network inaccessibility and disconnectivity during network dynamics. Oppositely, if the Trickle and ND algorithms are called frequently, but upon no topological changes (no mobility), network resources are just wasted.
We consider LPWN scenarios encompassing mobile and stationary nodes (APs). Fig. 1 illustrates the system model, where a MN moves from the vicinity of Node 8 toward Node 7. Mobile nodes are supposed to move freely, while maintaining their connectivity via a fixed infrastructure through hand-off. Hand-off is the process of switching from one point of attachment to another. We assume nodes (either fixed or mobile) have no location-awareness. Our evaluations will compare the support of mobility using soft and hard hand-off approaches, which are defined as follows:
– In a hard hand-off process, the current connection between a mobile node and an AP drops before a new connection is found and created.
– In a soft hand-off process, the connection between the mobile node and the new AP is activated before the current link is dropped.
Contributions. We provide fast and reliable mobility support in RPL. The proposed mobility solution, based on a hand-off mechanism, keeps the standard RPL protocol unchanged, while providing backward compatibility with the standard implementation, i.e. enabling the interoperability of standard and mobility-enabled nodes in the same network. The main contributions of this paper are as follows:
- 1.
Design a mobility management framework based on both soft and hard hand-off approaches, where hand-off designs are integrated within RPL/6LoWPAN.
- 2.
Analyze and validate the mobility management framework through analytical/probabilistic analysis.
- 3.
Implement and evaluate the mobility management framework in Cooja simulator.
We show that the proposed mobility management solution is able to keep packet delivery ratio close to 100%, while achieving very low average hand-off delay (≈ 4 ms). This is attained at the cost of more energy consumption of the APs (by keeping their radios on). We suppose that in many application scenarios, fixed nodes may be plugged to the power grid.
Organization. Section 2 explains the basics on RPL routing including terms, definitions and control messages. Section 3 gives a brief background on mobility support in IP-based LPWNs, which are based on mesh-under and route-over schemes [18]. These are followed by a short insight on our previous work smart-HOP (a protocol-agnostic hard hand-off mechanism) and mRPL (smart-HOP integrated within RPL) [19]. Section 4 proposes the new mobility management framework, while Section 5 presents its probabilistic model and evaluation. Section 6 further consolidates this evaluation through simulation in Cooja, comparing the performance of mRPL+ against mRPL and RPL. Finally, we conclude the paper in Section 7. Table 1 outlines the structure of the paper.
Section snippets
Background on RPL
RPL is an IPv6 distance vector routing protocol that is appropriate for low-power wireless networks with very limited energy and bandwidth resources. Considering the IEEE 802.15.4 as the underlying physical and link layer protocol, the data rate is less than 250 kbps and the communication is prone to high error rates, resulting in low data throughput. The RPL routing organizes nodes in a Destination Oriented Directed Acyclic Graph (DODAG) as depicted in Fig. 1. Each RPL router identifies a set
Related work
Traditionally, routing protocols in low-power networks with static nodes support joining and leaving of nodes. Similarly, RPL is also able to support adding and removing nodes. However, the process of detecting mobile nodes and maintaining the routing tree is very slow. Mobility is indicated as one of the main sources of inconsistency in RPL [23]. Generally, there are two main approaches that help in detecting mobility; (i) the DIO packet transmission, controlled by the Trickle algorithm [16],
Mobility management framework
In order to support mobility within a multi-hop LPWN, we devise a mobility management framework that provides timeliness, reliability and efficiency. In this framework; we (i) design two hand-off designs (soft and hard hand-offs), (ii) devise mechanisms to increase hand-off efficiency (hand-off features), (iii) develop improvements on RPL routing to increase the end-to-end performance during mobility (multi-hop add-ons), and (iv) evaluate the results, as depicted in Fig. 4. We define the main
Analytical model
Environmental characteristics may greatly affect network performance in low-power wireless networks. In this section, we extend the probabilistic analysis of smart-HOP [43] to a more general case that supports both soft and hard hand-offs. In this probabilistic analysis, we study the impact of two major channel parameters:
- 1.
path-loss exponent (η). It measures the power of radio frequency signals relative to distance.
- 2.
standard deviation (σ). It measures the standard deviation in RSSI measurements
mRPL+ vs. mRPL vs. RPL
The mRPL+ supports both soft hand-off and hard hand-off (mRPL), where these processes are provoked based on the network condition. RPL nodes can run any MAC protocol although a NullMAC that prevents turning radios off would conclude to a better network performance when a subset of nodes are moving. The reason is that the overhearing mechanism with NullMAC helps in activating the soft hand-off process that will in turn improve the network reliability and timeliness.
In mRPL+, during data
Conclusion
In this article, we proposed a mobility management framework that supports two distinct hand-off models; hard and soft models. In the soft hand-off model, the neighbor Access Points (APs) employ an overhearing mechanism to observe the link quality of the Mobile Node (MN). By detecting a high quality link at a neighbor AP, a beacon is transmitted to the MN, stating its willingness for serving as its future parent.
We evaluated and compared the performance of mRPL (hard hand-off within RPL) and
Acknowledgments
This work was partially supported by National Funds through FCT (Portuguese Foundation for Science and Technology) and by ERDF (European Regional Development Fund) through COMPETE (Operational Programme ’Thematic Factors of Competitiveness’), within projects FCOMP - 01 - 0124 - FEDER - 037281 (CISTER), FCOMP - 01 - 0124 - FEDER - 014922 (MASQOTS).
References (48)
- et al.
Smart-HOP: a reliable handoff mechanism for mobile wireless sensor networks
European Conference on Wireless Sensor Networks
(2012) - et al.
A high-throughput path metric for multi-hop wireless routing
Wireless Netw.
(2005) - et al.
Performance evaluation of mobile IPv6 over 6LoWPAN
ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks,
(2012) A mobility frame for 6LoWPAN WSN
IEEE Sensors J.
(2016)- et al.
RPL under mobility
IEEE Consumer Communications and Networking Conference (CCNC),
(2012) - et al.
Final report from the NSF Workshop on Future Directions in Wireless Networking
(2014) - E. Commission, Factories of the Future 2020: multi-annual roadmap for the contractual under Horizon 2020, Research...
- et al.
Definition of Cooperating Objects
(2012) - et al.
Mechanisms and challenges on mobility-augmented service provisioning for mobile cloud computing
IEEE Commun. Mag.
(2015) - et al.
Performance analysis of the ZigBee networks in 5G environment and the nearest access routing for improvement
Elsevier J. Ad-hoc Netw.
(2016)
Internet of things in the 5G era: enablers, architecture, and business models
IEEE J. Sel. Areas Commun.
Distributed mobility management for future 5G networks: overview and analysis of existing approaches
IEEE Commun. Mag.
The 6lowpan architecture
Proceedings of the 4th Workshop on Embedded Networked Sensors
RPL: Ipv6 routing protocol for low-power and lossy networks
Wiisard: A measurement study of network properties and protocol reliability during an emergency response
MobiSys
Real-time medical emergency response system: exploiting IoT and big data for public health
J. Med. Syst.
A proposal for proxy-based mobility in WSNs
Elsevier J. Comput. Commun.
PEGASIS: Power-efficient gathering in sensor information systems
Trickle: a self regulating algorithm for code propagation and maintenance in wireless sensor networks
Proceeding of the 1st USENIX/ACM Symposium on Networked Systems Design and Implementation
Neighbor Discovery for IP version 6 (IPv6), RFC 4861
Technical Report
mRPL: boosting mobility in the Internet of Things
RPL in a nutshell: a survey
Comput. Netw.
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