Wireless Sensor Network Protocol: Directed Diffusion

-

This protocol for WSN is a data centric query-based protocol where sink floods a query into the network through several routes between the sink and source. The sink supports one of those routes and receives data from that path within shorter time interval. Therefore, multipath delivery can be realized and significant achievement can be attained by adapting subset of network. 

The four features of directed diffusion routing protocol include Interests, data, gradients and reinforcement. The query that determines the user’s requirements is the Interest. Processed information is the data. The direction state of node that gets the Interest is the gradient. Multiple gradient paths are used to transmit events from originators of interest. The attribute value pairs that are used to name task descriptions are 
example:             type=wheeled vehicle                   //vehicle location
                              interval=20 ms                           //event sent every 20ms
                              duration=10s                              //next 10s duration
                              rect=[-100,100,200,400]            // sensors inside rectangle

Directed diffusion protocol builds path on need-basis and stores the data in attribute value pairs. Interest messages are broadcast (flooded) when sink requires data. This is added to neighbor’s interest cache and each neighboring node has gradients corresponding the ones that transmitted the interest. When a node generates data matching that interest, it is sent back to sink using gradients. The sink then reinforces shortest path and the intermediate nodes send the reinforcement by checking the local cache of the sent messages.

Advantages

  • It is data centric. The communication uses interests to identify named data. 
  • It performs neighbor to neighbor communication without node addressing mechanism. Every node specifies an end in the sensor network thus eliminating the need of routers and every node interprets data and interest messages. 
  • Each node is capable of performing caching and aggregation along with sensing thus saving energy and reducing delay substantially. Unlike IP-based sensor network, where a collection of specialized servers collect and process the sensor data, the network with directed diffusion protocol performs coordinated sensing close to the sensed phenomena thus providing robustness and scalability. 
  • Nodes require to distinguish between neighbors but are independent of unique addresses or identifiers. 
  • Global network topology is not required here and directed diffusion routing protocol is energy efficient.

Limitations

Data progressing takes place in intermediate nodes thus increasing the transmission latency in the directed diffusion protocol. Energy utilization is high in the protocol with respect to flooding and data processing. It uses directional flooding to set multiple paths. Data messages are transmitted redundantly through those paths. It then observes the path performance and reduces the path multiplicity. Thirdly, loop-free paths are not guaranteed through gradient setup mechanisms.

References

Handziski V., Köpke A., Karl H., Frank C., Drytkiewicz W. (2004) Improving the Energy Efficiency of Directed Diffusion Using Passive Clustering. In: Karl H., Wolisz A., Willig A. (eds) Wireless Sensor Networks. EWSN 2004. Lecture Notes in Computer Science, vol 2920. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24606-0_12

Comments

Post a Comment

Popular posts from this blog

IoT: Device Vulnerability & Security Concerns in Wearable Devices

-
Wearable IoT have broaden and improved the perspective of individuals about their surroundings. A successful IoT device has to be affordable as well as reliable. It should not interfere with other devices and should incorporate mechanisms to remain immune from interferences. It should further ensure effective battery life with perfect functionality and energy efficiency. However, the risks involved in attaining this ideal scenario are many. IoT include a plethora of devices or things like vehicles, smartphones, televisions, wearable devices like fitness tracking devices, smartwatch and Google Glass, etc. These devices are embedded with software applications, sensors and other components for receiving and sending data. A colossus of connected devices is created by inter-connectivity of those devices. This connectivity offers magnificent benefits to people’s lives but it entails certain security and privacy concerns. The most conspicuous among them are the wearable devices which are gain
Read more

Research Outlet: Industry Academia Collaboration Program

-
Image
In this era of new technologies emerging at an unprecedented fast pace, there is a binding need for collaboration between industry and academia. This article discusses the aspects of such alliance. Role of Academic I nstitut ions Academic I nstitut ions  serve both the industry and academia by providing a workforce, as well as furnishing innovative ideas to start new businesses. Therefore, the two are analogous to two banks of a river with their own independent sides. The two banks can be connected through bridges of science and engineering disciplines to contribute to the betterment of both—the industry and institutes. Therefore, institutes have to keep the curriculum in line with the changing needs of industry. Although it is not a quick and easy process but a continuous update in the syllabus shall keep the students and teachers at par with the demand in the market. The students learn the topics like testing, project leadership, management, professionalism and other skills within th
Read more

Artificial Intelligence in Patient Health Monitoring System

-
 Artificial Intelligence is the study and implementation of actions on computational devices which require human intervention. AI captures the intelligence and uses it in computation technology. Robert Plant stated “if Socrates is a man and all men are mortal, then it can be inferred that Socrates is mortal”. Similarly, AI works on the principle of transitive dependency. Human activities are recorded as the acceptable standard of decision making. Machine intelligence is built over those records and decisions are made by the intelligent machine which work very similar to humans. Basic Benefits to Healthcare workers and patients Software applications on Health care system are advantageous to the healthcare facilities, healthcare workers and patients. Some of the benefits of AI in health domain are The information can be quickly accessed with reduced errors. Healthcare workers can coordinate better among themselves reduced need of visiting healthcare facility AI offers better education an
Read more