5.3 Data-centric and hierarchical routing protocols

Data-centric and hierarchical routing protocols are key strategies for efficient communication in wireless sensor networks. These approaches optimize data transmission, reduce energy consumption, and extend network lifespans by minimizing redundant information and organizing nodes effectively.

Flat protocols like SPIN and Directed Diffusion use data negotiation and naming to reduce unnecessary transmissions. Hierarchical protocols like LEACH and PEGASIS organize nodes into clusters or chains, balancing energy use and streamlining data aggregation for improved network performance.

Flat Routing Protocols

Flooding and Gossiping

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• Flooding broadcasts data packets to all neighbors until destination is reached
  • Simple and easy to implement but can lead to implosion and overlap problems
  • Implosion occurs when duplicated messages are sent to the same node, causing unnecessary energy consumption
  • Overlap happens when two nodes sensing the same region send similar packets to the same neighbor
• Gossiping is an improvement over flooding where nodes send packets to a randomly selected neighbor instead of broadcasting to all
  • Reduces implosion but does not address the overlap problem completely
  • Still not energy-efficient as it does not consider energy constraints of nodes

SPIN (Sensor Protocols for Information via Negotiation)

• SPIN is a family of adaptive protocols that use data negotiation and resource-adaptive algorithms
  • Nodes assign a high-level name to their data called meta-data, which is used to negotiate with each other before transmitting
  • Ensures only useful information will be transferred, reducing redundant data and saving energy
• Three types of messages used in SPIN:
  • ADV: When a node has data to share, it broadcasts an ADV containing the meta-data
  • REQ: A node interested in the data sends an REQ message
  • DATA: The actual data is sent to the requesting node
• Advantages of SPIN include eliminating redundant data transmissions and minimizing energy consumption through negotiation

Directed Diffusion

• Data-centric routing protocol where data generated by sensor nodes is named by attribute-value pairs
  • A node requests data by sending interests for named data
  • Data matching the interest is then "drawn" down towards that node (diffusion)
• Directed Diffusion has four key elements:
  • Naming: Attribute-value pairs are used to name data and match it with interests
  • Interests and Gradients: An interest is a query or interrogation which specifies what a user wants
    • Each node establishes a gradient towards the neighbor from which it receives the interest, forming multiple paths
  • Data Propagation: Data is propagated along the interest's gradient path, being aggregated at intermediate nodes
  • Reinforcement: To accommodate long-lived interests, the path with the highest data rate is reinforced to prevent further flooding

Hierarchical Routing Protocols

LEACH (Low-Energy Adaptive Clustering Hierarchy)

• LEACH is a clustering-based protocol that utilizes randomized rotation of cluster-heads to evenly distribute the energy load
  • Nodes organize themselves into local clusters, with one node acting as the cluster-head
  • Cluster-heads compress data arriving from nodes and send an aggregated packet to the base station, reducing energy consumption
• LEACH operates in two phases:
  • Setup Phase: Clusters are organized and cluster-heads are selected randomly
  • Steady Phase: Data is sent to the cluster-heads and then to the base station
• Advantages of LEACH include:
  • Cluster-heads aggregating data, reducing the amount transmitted to the base station (sink)
  • Cluster-heads changing randomly, distributing energy consumption evenly across all nodes

PEGASIS (Power-Efficient Gathering in Sensor Information Systems)

• PEGASIS is an improvement over LEACH, forming chains of sensor nodes instead of clusters
  • Each node communicates only with a close neighbor, taking turns transmitting to the base station
  • Gathered data moves from node to node, aggregated and eventually sent to the base station
• The chain can be constructed using a greedy algorithm or the base station can compute the chain and broadcast it to all nodes
• Advantages of PEGASIS:
  • Reduces the amount of data that must be transmitted to the base station
  • Distributes energy consumption evenly as each node takes turns being the leader

TEEN (Threshold-sensitive Energy Efficient sensor Network protocol)

• TEEN is designed for time-critical applications, transmitting only when a sensed attribute crosses a certain threshold
  • Utilizes a hierarchical approach with closer nodes forming clusters (first level)
  • Cluster-heads then form the second level, until the sink is reached
• Two thresholds used in TEEN:
  • Hard Threshold (HT): The absolute value of the sensed attribute to trigger a sensor node to switch on its transmitter and send data
  • Soft Threshold (ST): The small change in the value of the sensed attribute that triggers the node to transmit data again
• Advantages of TEEN include suitability for time-critical sensing applications and increased energy efficiency as data is only transmitted when thresholds are crossed

Data Aggregation Techniques

• Data aggregation is a process of aggregating the sensor data using aggregation approaches
  • Aims to reduce the energy consumption by minimizing the number of transmissions
• Different data aggregation techniques can be used depending on the network architecture and application requirements
  • Centralized Approach: An aggregator node collects data from all other nodes, aggregates it, and then transmits to the sink (base station)
  • In-Network Aggregation: Aggregation is done at intermediate nodes as data is forwarded towards the sink, reducing the amount of data transmitted
  • Tree-Based Approach: Nodes are organized into a tree, with aggregation being performed at intermediate nodes and the root transmitting the final data to the sink
• Advantages of data aggregation include:
  • Reducing the number of transmissions, thereby saving energy and prolonging network lifetime
  • Eliminating redundancy, minimizing data transmission, and improving bandwidth utilization