Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications
Abstract
:1. Introduction
- This paper integrates edge computing with opportunistic networking for disaster recovery;
- The sensors in the network process and aggregate data locally to reduce the amount of data transmitted;
- The sensors create density-based clusters where sensors with the most neighboring nodes become cluster heads. This approach reduces the number of data collectors and transmitters and distributes energy consumption equally over sensor nodes;
- The nodes, which are not part of any cluster (e.g., isolated nodes) opportunistically forward data to the forwarder nodes. These nodes, while moving, join to the cluster closest to them;
- If any node moves out of a cluster due to mobility, the cluster restoration process starts based on the node’s property, called the minimum period of connectivity (MPC). This property ensures an energy efficient cluster restoration process compared to the cluster restoration process of existing protocols, which involve all nodes in cluster restoration at the end of each round.
2. Related Work
3. Proposed Opportunistic Routing Protocol
3.1. Terminologies
3.2. Form Density-Based Clusters
Algorithm 1 (cluster formation) |
Input: node x, MPCg, minimum number of nodes in a cluster (minNode). Output: a cluster with a cluster head CH. |
begin 1: N← GetNeighbors(x) //find number of neighbors of node x 2: weight ←GetWeight(x) //find weight of node x and all other nodes using Equations (2)–(4) 3: If |N| minNode 4: Select x as a core point //i.e., a good candidate to be a CH 5: if weight(x) ≤ weight (y), 6: select x as CH of cluster C 7: minNode = |N| // minNode is set to the number of neighbors of node x 8: end if 9: else 10: select x as border point // if weight of x is greater than all its neighboring nodes 11: end if 12: for each y∈N do 13: if y is not CH nor member of any cluster 14: if (MPCx,y ≥ MPCg) 15: C←{y}; include y in the cluster C // y is in cluster C if its MPC greater than global MPC 16: else 17: select node y as a noise to C 18: end if 19: end if 20: return CH 21: Repeat steps 1–20 until all clusters are formed 22: end |
3.3. Routing
3.4. Cluster Restoration
Algorithm 2 (Cluster Restoration) |
Input: y is a border point from a neighbor cluster to C, C is a cluster to be connected to y, MPCg is the minimal period of connectivity. |
Begin 1: Find x such as MPC y, x = Max, where x is a noise 2: Relay x = FindBestCandidate(y, x), where x noise & MPCy,x is a max 3: if x is Member(C) then //Scenario 1 4: y.increaseRc(getMPC(x, y), MPCg) // increase Rc of y to maintain MPC x,y, same as MPCg 5: else //Scenario 2 6: temp = min(getMPC(x,y), getMPC(x,C)) 7: y.increaseRc(temp, MPCg) 8: end if 9: end |
4. Performance Evaluation
4.1. Computation Efficiency
4.2. Energy Efficiency
5. Simulation Model, Setup and Results
5.1. Energy Model
5.2. Network and Mobility Model
5.3. Performance Metrics
- Energy consumption is the total energy consumed by the sensor nodes in the network over a number of rounds.
- Throughput is the amount of data transmitted by a node per second. We calculate throughput in Gigabytes/second in this paper.
- Packet delivery ratio is the ratio of the total number of packets delivered to the total number of packets transmitted.
- Packet loss ratio is the ratio of the total number of packets lost to the total number of packets transmitted.
5.4. Simulation Results
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Parameter | Value |
---|---|
Simulation network area | 2000 × 2000 m2 |
Number of node | 100 |
Communication range of a node | 200 m |
Transport protocol | UDP |
MAC protocol | IEEE 802.11 |
Mobility Model | Random |
Mobility Speed | 5 m/s |
Pause time | ½ s |
Duration of a round | 200 s |
Traffic type | Constant Bit Rate (CBR) |
Data transmission rate | 250 Kbit/s |
Data packet size | 128 Bytes = 1 Kbit |
Features | LEACH | TEEN | LORA | ODCR |
---|---|---|---|---|
Cluster formation is done at the end of each round | √ | √ | X | X |
All nodes in the network involve in cluster restoration or reform | √ | √ | X | X |
Nodes that connect or communication other nodes for a longer period time are good candidate to be selected as cluster head | X | X | √ | X |
Consider mobility of nodes | X | X | √ | √ |
Construct candidate zone at each with a number of forwarder nodes | X | X | √ | X |
Requires reselecting forwarder nodes very often due to mobility | X | X | √ | X |
Use opportunistic forwarding as a cluster member or isolated nodes | X | X | X | √ |
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Al-kahtani, M.S.; Karim, L.; Khan, N. Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications. Electronics 2020, 9, 455. https://doi.org/10.3390/electronics9030455
Al-kahtani MS, Karim L, Khan N. Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications. Electronics. 2020; 9(3):455. https://doi.org/10.3390/electronics9030455
Chicago/Turabian StyleAl-kahtani, Mohammed S., Lutful Karim, and Nargis Khan. 2020. "Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications" Electronics 9, no. 3: 455. https://doi.org/10.3390/electronics9030455
APA StyleAl-kahtani, M. S., Karim, L., & Khan, N. (2020). Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications. Electronics, 9(3), 455. https://doi.org/10.3390/electronics9030455