Collaborative routing and data delivery architecture for commercial wireless sensor networks
© Hasani et al.; licensee Springer. 2013
Received: 7 April 2012
Accepted: 10 February 2013
Published: 28 February 2013
Lately, wireless sensor network applications have emerged for provision of commercial services to end users. This results in commercial deployment of sensor networks which is as an important research area due to a number of design and quality of service challenges. An important technical challenge for sensor service provision to end users is managing dynamic network conditions such as unreliability of sensor nodes and network links which results in frequent service outages. This research is aimed at addressing this challenge. It presents a novel architecture which utilizes the availability of multiple sensor networks under different administrative domains, deployed in an area such that maximum network connectivity and high service availability are ensured. The architecture incorporates modifications and enhancements at the medium access control and the routing layers of sensor nodes for the collaborative operation of sensor networks. The design is based on IEEE 802.15.4 standard and ad hoc on demand distance vector routing protocol. The proposed architecture is mathematically analyzed with regards to overheads associated with the design such as routing and communication, and techniques to minimize these overheads are recommended. Through simulations using OMNET++, we show that the proposed architecture effectively provides connectivity for disconnected nodes achieving an overall increase in throughput for all the cooperating networks.
KeywordsCollaborative routing Architecture Commercial sensor networks
Low-rate wireless personal area networks (LR-WPANs) such as IEEE 802.15.4 typify the more generalized form of wireless sensor networks (WSNs) with their unique design space. These networks comprise small, low power, low cost, and multi-functional sensing devices working in collaboration for sensing and data delivery under robust network conditions. These features render the design of WSN challenging as compared to the conventional networks. The design requirements in WSN that have consistently been addressed by the research community are energy efficiency, scalability, and adaptability to varying network conditions such as unreliable sensor nodes and flaky communication links. The design is also influenced by the type of sensing application and its specific demands. Lately, bulk manufacturing of inexpensive sensor node hardware has resulted in commercial deployment of these networks in order to provide on-demand sensor services to end users. Analogous to the fast proliferation of cellular network services to end users owing to mass production of low-cost mobile handsets, we anticipate swift commercial deployment of sensor networks for sensor services in the near future because research efforts are now rapidly directed towards designing concurrent applications for sensor networks and technical support for commercial sensor services [1–6].
Various experimental or commercial sensor networks that have been deployed lately support applications like vehicle tracking, industrial surveillance, home automation, seismic activities monitoring, remote health monitoring for patients, and even wildlife tracking. Similar to the simultaneous co-existence of multiple cellular networks in the same coverage area with distinct, at times overlapping clientage, it is expected that in near future multiple sensor networks with different sensing capabilities would co-exist in the same area. This anticipated scenario opens a new research dimension concerned with the co-existence of multiple sensor networks in the same geographical area which is maintaining quality of service for commercial users in the presence of link outages and limited resources. As of now, the research efforts directed towards addressing this issue remain insufficient. This mandates the attention and focus of the scientific community to design protocols and applications for co-existing sensor networks from the perspective of performance enhancement and reliability of services .
In order to minimize service outage, commercially deployed voice and data networks maintain backup links and hardware thus mitigating the effects of possible failure of primary links or hardware. Since the idea of multiple co-existing sensor networks is new, the contemporary failure resilience efforts in WSN are geared to provide similar forms of redundancy. However, such over-provisioned sensor networks remain vulnerable to unpredictable scope and gravity of failures, raising questions on the very viability of this approach. In this article, we present a collaborative routing and data communication architecture for co-existing sensor networks that aims to resolve network outage problems due to coverage holes and maintains symbiotic backup connectivity of participating networks. The architecture proposes modifications both at the medium access control (MAC) layer and the network layer of sensor nodes. MAC layer changes are required for managing traffic flows for shared channel communication while modifications in the routing protocol are necessary to maintain and collect important management information for co-existing sensor networks. We analyze the proposed design in terms of various associated overheads and show that the architecture achieves the desired objectives with an acceptable increase in overheads.
There are three basic design elements of the proposed architecture.
MAC layer design: MAC layer algorithmic changes are required to realize native and foreign-channel access by multiple WSNs. A disconnected sensor node or even a group of such sensor nodes utilize the presence of other networks’ nodes in its transmission range, communicating with them using certain channels. Algorithmic modifications are proposed in association procedure that allows native and foreign channel access and scheduling of nodes of co-existing sensor networks.
Routing protocol design: Algorithmic changes are incorporated in the implementation of routing protocol in order to make multiple sensor networks mutually beneficial. The idea is to give sensor nodes the provision to employ nodes of other sensor networks for route discovery and data delivery.
Overhead modeling: The proposed architecture is mathematically modeled in terms of energy overheads associated with MAC layer design and routing.
The remainder of the article is organized as follows. In Section 2, we discuss the related work. Section 3 defines the problem. In Section 4, we present comprehensive design of our proposed architecture. Section 5 presents mathematical analysis of proposed architecture in terms of various overheads. Section 6 presents simulation results using OMNET++. Finally Section 7 concludes the article.
2. Related work
The collaborative design of multiple sensor networks located in an area is a novel idea. Multi-application sensor networks and multi-channel communication, where a single WSN can switch channels for data communication, can be found in the literature. This concept forms the baseline implementation of our idea. We review the related work in this section. Multi-application WSN is a network formed by sensor nodes that are equipped with multiple sensors and different applications run over these nodes independently. The research work in this domain relates to the software design aimed at efficiently utilizing the hardware resources of a sensor node. In an earlier work , we presented the guidelines to bind multiple applications over a single sensor network at run time. The idea of virtual sensor network proposes virtualization of multiple applications running over a single sensor network . Yu et al.  support concurrent application provisioning on a sensor network with an emphasis on over-the-air programming prospects. Mottola and Picco  propose a programming abstraction as a mean to support multiple applications over a single sensor network. Tsetsos et al.  discuss network architecture for sensor-based services and develop business model for such applications. Heinzelmanet al.  present middleware design to support multiple applications considering various real-life application scenarios. Bhattacharya et al.  present utility-based multi-application allocation and deployment environment as an integrated application deployment system for sensor network applications sharing the same infrastructure. Alomar and Akbar  propose a routing mechanism named “Carrefour Cast” that is based on aggregated ‘Route Requests’ and ‘Route Replies’ in order to decrease routing overhead in multi application set-up in multiple gateway environments. They optimize multiple applications provisioning by proposing network layer modifications.
In IEEE 802.15.4 standard, multi-channel communication is proposed for communication over multiple channels, and we use this design at the MAC layer in our proposed architecture for communication of co-existing WSNs. Multi-channel communication is an established operational requirement in wireless ad hoc and sensor networks. Jain et al.  and Li et al.  present the idea of a dedicated control channel for negotiation of data channel access and synchronization for ad hoc networks. Ramakrishnan and Ranjan  present a sensor multi-channelMAC protocol for WSNs in a contention-based scheme that works with one control channel and eight data channels. MC-LMAC  is proposed for WSNs based on dedicated control channel but the goal is to maximize throughput using coordinated transmission over multiple frequency channels by scheduled access, where each sensor node is granted a timeslot and transmits without contention. Zhou et al.  propose multi-frequency MAC protocol for WSN viewed as one of the initial multi-channel MAC protocols designed for WSN. It is a slotted CSMA protocol where nodes contend for the medium before they transmit at the beginning of timeslot. Y-MAC  is another recently proposed multi-channel MAC protocol designed for WSNs that is based on scheduled access. Timeslots are assigned to receivers instead of senders and potential senders for the same receiver contend for medium at the beginning of each timeslot.
Recently, some researchers have investigated the usage of multiple channels to defy the limitations of single channel MAC protocols. In this regard, Ansari et al.  and Liu and Wu  designed a multi-radio MAC protocol, running on a sensor node platform equipped with two radio transceivers. This approach is economically unsuitable for WSNs due to an increase in hardware cost, battery consumption, and design complexity. Moreover, a multi-channel MAC protocol using single radio transceiver is fairly plausible since most commercial radio devices such as CC1000  and CC2420  provide programmable channel selection to support multiple channel operation.
3. Problem definition
WSNs are being deployed commercially for providing on-demand sensor services to end users. Consider an example scenario where three or more sensor service providers manage their sensor networks that are deployed for providing certain services. One of the networks provides area surveillance services for security the second network provides environmental monitoring services while third is a visual sensor network meant for providing images. If all of these networks happen to be co-located such that a number of nodes overlap, these networks are the potential candidates for implementing the collaborative design proposed in this study.
4. Proposed architecture
In this section, we elaborate the architectural details of the framework by defining the design elements, making necessary assumptions, and giving details of the proposed MAC layer algorithm and routing protocol.
4.1 Design elements
The basic design considerations for cross-network communication from technical and economical viewpoints are as follows:
The operator’s first choice must be its home network, switching to cross-network communication only when home network is not available.
The design must be mutually beneficial for all co-operating sensor networks. A sensor network offers routes to other networks while utilizing the routes through them for connectivity of its isolated nodes.
The participation of nodes in cross-network communication must not be overwhelming compared to their participation in native network operations. There must be well-defined criteria to distinguish traffic these nodes carry for the native network from the cross-network traffic. Such criteria would ensure to limit packet processing at nodes that are not supposed to handle the cross-network traffic otherwise the design would not remain economically feasible for native network operations.
The design must be transparent to the application and transport layer of nodes executing the applications.
The new set of algorithms and protocols for cross-network communication must be based on existing standard protocols.
The design must be simple to integrate medium access, routing and data delivery algorithms and protocols.
4.2. Design assumptions
The proposed architecture is based on few assumptions listed below.
Sensor nodes operate in low duty cycle to save energy thus ensuring long network life.
Each sensor network has gateway(s) and the data communication takes place between sensor nodes and gateway.
We assume fixed channel assignment instead of dynamic channel assignment in sensor networks in order to minimize interference and reduce complexity.
The data communication paradigm can be event based (triggered by sensor nodes) or on demand (triggered by gateways).
The reconciliation of co-existing networks is managed through wired inter-connection in order to exchange information related to co-operative routing and data communication.
The networks operate using non-overlapping addressing schemes such that a sensor node can identify a packet by the addressing scheme of source/destination.
4.3. MAC layer design
At the MAC layer, basic operation of IEEE 802.15.4 standard for LR-WPANs remains unchanged while algorithmic modifications and enhancements are incorporated in order to realize communication between different sensor networks. MAC Layer design is illustrated in the following sections.
4.3.1. Channel assignment for co-existing sensor networks
4.3.2. Implementation of shared channel connectivity
In IEEE 802.15.4 standard , it is stated that SO and BO are selected based on the following equation 0 ≤ SO ≤ BO ≤ 14. For energy-efficient operation, it is essential to maintain SO less than BO. If SO is less than BO by a minimal value of 1, the resulting duty cycle from Equation (2) is found to be 50%. The highest possible duty cycle with energy saving is 50% and that corresponds to the case when active period is equal to inactive period. Such a long inactive period can be utilized to schedule another instance of super-frame structure working independently to the already running super-frame. Such scheduling is achieved through a priori synchronization amongst the sensor networks such that the two super-frames operate in the two frequency channels independently, one in native channel and the other in shared channel. Every node, no matter to which native channel it belongs, switches to the shared channel and expects an orphaned message  from a disconnected node to arrive. A node disconnected from its native channel can now use the common channel to associate to such a node in order to establish a connection to its parent network. This connectivity is intermittent and persists only within the superframe duration. The disconnected node gets to access its respective gateway through such borrowed connectivity. This is a simple and low-cost approach to implement shared channel connectivity between nodes of co-existing sensor networks.
4.4. Routing protocol enhancements
The design of routing protocol is an important part of the proposed architecture because it deals with minimizing the routing overhead, ensuring end-to-end data delivery, and defining the rules of interaction among co-existing networks. The network layer enhancements are not concerned with routing engine but relate to the maintenance and aggregation of charging and billing information at each network provider’s end. A sensor network first attempts to discover a route through its native channel. In case of success in route discovery through native network, assistance from co-existing sensor networks is not required. But when that fails, the sensor node or gateway switches to common channel for route discovery. The design of routing protocol accommodates billing and charging information in routing and data packets while keeping data and communication overhead as low as possible. Although we select ad-hoc on demand distance vector (AODV) routing protocol for the proposed enhancements due to its application in sensor and ah-hoc networks but these modifications are simple and generic and can also be implemented in other routing protocols.
4.4.1. Route discovery
In AODV protocol, the route discovery process involves flooding of Route REQuest (RREQ) and unicast of Route REPly (RREP) to RREQ originator. The route discovery process for modified routing protocol is discussed as follows:
Route request: The modified RREQ packet is shown in Figure 5a. The field ‘Nets’ is added before ‘hop count’, and ‘trailer information’ about contributing networks is appended at the end of the packet. ‘Nets’ represents the number of networks, other than native network that have forwarded the RREQ packet. If the packet is only processed by the native network (e.g., when packet is sent via native channel) the value in ‘Nets’ would be zero which means packet has no trailer information and is only using the native network resources. The trailer is appended to represent the networks that have forwarded the RREQ packet. Each network that forwards or broadcasts the packet inserts its unique 8-bit network ID and count of packet relay (8-bit “relay count” field). Thus, the ‘Nets’ value reports the number of exterior networks that participate in packet transmission and the trailer entries that are appended at the end of the packet provide information about those exterior networks.
Route reply: Route reply process is similar to the single sensor network route reply process with the same modifications as described in route request process. The role of ‘Nets’ value and packet trailer information is same as described in RREQ packet format and the packet format for RREP is shown in Figure 5b.
Algorithm at sensor node: The sensor node runs an algorithm for common channel route discovery which is simple and is explained as follows:
If a packet arrives through flooding and requires response, the sensor node sends response packet with ‘Nets’ field set to zero without any trailer information. An example of this case is the arrival of RREQ packet.
If a packet arrives through unicast and requires response, the sensor node sends response packet with the same value of ‘Nets’ and trailer fields as in the arriving packet. This way the gateway is informed about the complete forwarding information of packet round trip. An example of this case is receiving data packet.
RREP and ACK packets do not require response thus there is no special handling for these packets at the sensor node. Data packets are not part of the route discovery process and are discussed later.
4.4.2. Gateway functionality
The gateways are unconstrained devices in terms of resources and administer cross-network communication. The gateways play an additional role in the routing activity which is discussed in this section.
Route discovery process
During the route discovery process, the gateway tracks the record of relays by foreign network nodes through ‘Nets’ field, corresponding Net IDs and their relaying counter. Two possible scenarios in route discovery are:
If route discovery is initiated by sensor nodes, receiving gateway records external network relays listed in RREQ packet. The gateways distinguish RREQs by RREQ source address and RREQ ID. If RREQ is not already registered with gateway, it registers it in database and responds with RREP. If already registered, it updates the record. This gives an accurate measurement of reverse path and related data path cost.
If route discovery is initiated by either of the gateways, all gateways broadcast RREQ with same RREQ ID because destination node is unknown. The destination node responds to first arriving RREQ as per AODV, and RREQ corresponds to the path between node and closest gateway. The closest gateway notifies the originator gateway if it is not the originator of RREQ packet itself. RREP informs gateway about the cost of RREP.
Management information sharing
Each sensor network belonging to an operator is associated with a management and database server. The central database server is linked with each gateway and records attributes of the shared network resources. Individual database servers of each network operator are connected to the central database server in order to exchange pricing information. The gateway upon receiving a packet through shared channel updates its database server. These databases are RREQ database and unicast database (Figure 6). RREQ database records the arrivals of RREQ packets. A gateway may receive duplicate RREQ through different paths as a result of flooding but RREQ arriving through the shortest path is added in database after ensuring that RREQ is not registered at other gateways of the same operator. ‘Gateway ID’ is the destination address of the receiving gateway that responds to the RREQ through the shortest path. ‘Source Node ID’ is the ID of the node originating RREQ and ‘RREQ ID’ is the ID of the RREQ packet. Hop count is the minimum hop count value in arriving RREQs. ‘Relay count’ is the hop count in foreign networks identified through their respective ‘Nets’ fields (see Figures 5 and 6). For each arriving RREP or data packet, the gateway updates the unicast database for recording the cost of traversal. This method is useful for measuring the cost of transmission of packets in unicast since the exact number of forwarding by each network is retained in the packet. Figure 7 gives the algorithm at gateway to handle RREQ, RREP or data packets. The database information is periodically updated by individual database servers at the central database server for reconciliation of revenue based on predefined network resource sharing agreement.
4.4.3. Handling route errors
4.4.4. Data delivery process
The data delivery process initiates after a route is established. To estimate the cost of data delivery in shared channel, modified header and trailer are used in combination with the underlying network layer protocol of sensor network. Traditional networks use Internet Protocol (IP) as the network layer protocol but it is highly inappropriate for sensor networks due to large packet overhead and many functions not required in sensor networks. IEEE 802.15.4 can handle a maximum payload of 127 bytes so smaller or compressed versions of headers are used at network layer. uIP  is an example of such IP version which can be modified to record number of contributing networks and their respective ‘relay count’ in common channel by using ‘Nets’ field in the header and trailer information. The algorithms given for sensor nodes and gateways for routing also apply to data packets.
5. Mathematical analysis
In this section, we mathematically analyze our proposed architecture. We estimate overhead due to MAC layer and routing layer enhancements for the framework which establishes two logical networks to which a sensor node belongs and evaluate additional costs associated with this collaborative design. Optimizations to minimize overheads are also suggested. The packet overhead associated with the collaborative design is also analyzed.
5.1. Overhead at MAC layer
The overhead factor between energy consumption in conventional sensor network design and our proposed design is SD2/SD1. Equation (5) shows that the energy overhead in collaborative design can be minimized by keeping SD2 low. Although keeping SD2 low causes reduction in throughput and increased transmission delay, nonetheless this may be an acceptable option considering the availability of a shared channel backup.
Parameters for plots in Figure 11 (SD 1 versus E s and SD 1 versus E d )
1.92 s (for BO = 7)
(a) 0.015 s (for SO = 0) to 0.48 s (for SO = 5)
(b) 0.015 s (for SO = 0) to 0.96 s (for SO = 6)
(a) 0.06 (for SO = 2)
(b) 0.03 (for SO = 1)
Parameters for plots in Figure 12 (SD 2 /SD 1 versus E d )
1.92 s (for BO = 7)
(a) 0.48 s (for SO = 5)
(b) 0.96 s (for SO = 6)
(a) 0.015 s (for SO = 0) to 0.06 (for SO = 2)
(b) 0.015 s (for SO = 0) to 0.03 (for SO = 1)
5.2. Overhead at routing layer
Parameters for co-existing sensor networks
Total number of networks
Number of nodes of a sensor network
Area of deployment (in m2)
Node density for a single sensor network (nodes per unit area)
Transmission radius of node (in meter)
Average rate of route requests/node for sensor network
If area and transmission radius remain constant, increasing the number of nodes results in improved connectivity. It is clear from (8) that in shared channel connectivity, the effective number of nodes is large and the probability of connectivity is close to 1.
Example of parameters of thee co-existing sensor networks
Number of nodes
Transmission radius (m)
Equation (12) shows that is an additive overhead factor as compared to overhead in normal flooding. Thus, routing overhead which corresponds to flooding by nodes of all co-existing networks is excessively increased. The flooding cost for nodes of recipient network is not much increased but the co-existing networks receive a large number of packets to be forwarded. This analysis reinforces the routing overhead conclusion drawn earlier where Figure 13 shows that having too many nodes in an area does not improve connectivity as connectivity probability saturates beyond a particular node density.
5.2.1. Routing overhead optimization
This shows that all networks participate equally in terms of the effective number of nodes for gossiping-based shared channel connectivity. Gossiping results in reducing the number of nodes forwarding RREQ packets from 205 to 100 which reduces the cost of route discovery process thus minimizing routing overhead associated with shared channel communication.
5.3. Packet overhead
where βk/P is the additive overhead factor and is inversely proportional to packet size in single sensor network operation. The selection of an appropriate packet size is an open research issue in sensor networks. A larger packet size reduces data overhead but is more susceptible to packet losses due to noisy medium. Maximum payload allowed in IEEE 802.15.4 is 127 bytes and it corresponds to minimum packet overhead based on (16).
6. Simulation results
OMNET++ simulations setup
Total number of sensor networks
1000 × 1000 m2
Number of nodes in area
Number of nodes in observed network
6.1. Impact of collaborative design on connectivity of nodes
6.2. Impact of number of disconnected nodes on performance of collaborative design
6.3. Impact of collaborative design on throughput
Commercial sensor networks are aimed at providing persistent and stable sensor services to the end users. However, this type of service provision is negatively affected by the uncertain network conditions like node and link failures. This results in network partitions resulting in frequent undesirable service outages or unavailability of sensed data. In a scenario where multiple sensor networks overlap within a geographical area which may or may not be under the same administrative control, these networks could be enabled to utilize mutual resources in order to ensure desired network performance and quality of service. We presented a routing and data delivery architecture for mutually beneficial collaborative operation of commercial sensor networks with IEEE 802.15.4 and AODV as the building blocks. We conclude that collaborative operation of commercial sensor networks results in ensuring connectivity of isolated nodes and is mutually beneficial for all participating networks. We plan to take up pricing issues for the proposed collaborative design as future work.
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