1. Sensor Network Data Dissemination based on the paper titled Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks Presented by Baha’a Al-Deen Omar Student I.D: 0037224

2. 1- Introduction What is data dissemination? It is the delivery of data between network nodes from source to destination. It is the delivery of data between network nodes from source to destination. What is Sensor network? It is a set of communication nodes planted, without previous planning, in the environments in which we need to collect data and provided with various types of sensors to collect the needed information. It may also contains processing unit to process data or used only to transmit time series of the sensed phenomena to other node. It is a set of communication nodes planted, without previous planning, in the environments in which we need to collect data and provided with various types of sensors to collect the needed information. It may also contains processing unit to process data or used only to transmit time series of the sensed phenomena to other node.

3. 2- Distributed Sensor Networks Advances in processors, memory and radio technology will enable small and cheap nodes capable of wireless communication and significant computation. Advances in processors, memory and radio technology will enable small and cheap nodes capable of wireless communication and significant computation. Beside the sensing ability of these nodes, distributed microsensing can be achieved- a collection of nodes can coordinate to achieve larger sensing tasks, or collaborate to disambiguate a certain sensed phenomena. Beside the sensing ability of these nodes, distributed microsensing can be achieved- a collection of nodes can coordinate to achieve larger sensing tasks, or collaborate to disambiguate a certain sensed phenomena.

4. 2- Sensor Networks-- continue Due to the low cost of these nodes, tens of them can be deployed near the phenomena to be sensed, in unplanned fashion. Due to the low cost of these nodes, tens of them can be deployed near the phenomena to be sensed, in unplanned fashion. Despite of their low cost, these nodes can provide high SNR. Despite of their low cost, these nodes can provide high SNR.

5. 2- Sensor Deployment Categories Large and complex sensor networks. These are usually deployed far from the phenomena to be sensed, so they must afford complex signal processing algorithms to separate the environmental noise from the targets. Large and complex sensor networks. These are usually deployed far from the phenomena to be sensed, so they must afford complex signal processing algorithms to separate the environmental noise from the targets. Less complicated sensor networks. The node here only transmits a time series of the sensed phenomena and do not posses any computational capability. These time series data is sent to one or more nodes which performs the data reduction and filtering. Less complicated sensor networks. The node here only transmits a time series of the sensed phenomena and do not posses any computational capability. These time series data is sent to one or more nodes which performs the data reduction and filtering.

6. 2- Sensor Networks-- continue Because sensors are battery-powered, saving battery power is a very important requirement. This means that using a short- term communication is preferred over long-term communication. The short-term communication also helps in communicating around obstacles. Because sensors are battery-powered, saving battery power is a very important requirement. This means that using a short- term communication is preferred over long-term communication. The short-term communication also helps in communicating around obstacles. These power consideration and other communication capabilities lead to a different sensor network organization. In this paper the waveform from the target in converted into event description, and the request for a specific data is called an interest. These power consideration and other communication capabilities lead to a different sensor network organization. In this paper the waveform from the target in converted into event description, and the request for a specific data is called an interest.

7. 3- Directed Diffusion Data is named using attribute-value pairs. Data is named using attribute-value pairs. A sensing task is disseminated throughout the sensor network as an interest (task description) for the named data. A sensing task is disseminated throughout the sensor network as an interest (task description) for the named data. This dissemination sets up gradient (paths) to draw events (data matching the interest). This dissemination sets up gradient (paths) to draw events (data matching the interest). Events start to flow towards the originators of the interest, called sink, along multiple paths. Events start to flow towards the originators of the interest, called sink, along multiple paths. The sink then reinforce, one or smaller number of these paths. The sink then reinforce, one or smaller number of these paths.

8. 3.1 Naming Task description are named using a list of attribute-value pairs that describe a task. Task description are named using a list of attribute-value pairs that describe a task. The following is a request to find a four-legged animal in a certain region for the next 10s for every 10ms. The following is a request to find a four-legged animal in a certain region for the next 10s for every 10ms.

9. 3.1 Naming--continue When the node receive this interest, it uses it’s sensors to collect the desired information and are sent back to the sink node. When the node receive this interest, it uses it’s sensors to collect the desired information and are sent back to the sink node.

10. 3.1 Naming--continue It is obvious that selecting a naming scheme is the first step in designing such networks. Here we used attribute-value pairs. Other naming schemes such as hierarchical can be used. It is obvious that selecting a naming scheme is the first step in designing such networks. Here we used attribute-value pairs. Other naming schemes such as hierarchical can be used. The naming scheme can affect the expressivity of tasks and can affect the performance of a diffusion algorithms. The naming scheme can affect the expressivity of tasks and can affect the performance of a diffusion algorithms.

11. 3.2 Interests an Gradients The interval specifies the data rate. The interval specifies the data rate. The sink node periodically broadcast the interest message to it’s neighbors. The sink node periodically broadcast the interest message to it’s neighbors. An initial interest is transmitted with attributes exactly the original message but with larger interval (lower data rate). This is supposed to be exploratory; it tries to determine if there are any sensor node that detect a four-legged animal. An initial interest is transmitted with attributes exactly the original message but with larger interval (lower data rate). This is supposed to be exploratory; it tries to determine if there are any sensor node that detect a four-legged animal.

12. 3.2 Interests an Gradients-- continued The sink periodically transmits the interest with monotonically increasing timestamp. This is necessary because interest are nor reliably transmitted through the network. The sink periodically transmits the interest with monotonically increasing timestamp. This is necessary because interest are nor reliably transmitted through the network. Every node contains an interest cache. Each item in the cache refers to a distinct interest (all the attribute differs for each interest). Every node contains an interest cache. Each item in the cache refers to a distinct interest (all the attribute differs for each interest). Two identical interest maybe represented in a single interest entry. Two identical interest maybe represented in a single interest entry.

13. 3.2 Interests an Gradients-- continue Each interest entry has a timestamp that indicated the last received matched interest. Each interest entry has a timestamp that indicated the last received matched interest. Contains several gradients, up to one per neighbor. Each gradient contains a data rate field requested by the specified neighbor, derived from interval attribute. Contains several gradients, up to one per neighbor. Each gradient contains a data rate field requested by the specified neighbor, derived from interval attribute. It also contains a duration field, derived from the timestamp and the expiresAt attributes. This field indicates the life time of the interest. It also contains a duration field, derived from the timestamp and the expiresAt attributes. This field indicates the life time of the interest.

14. 3.2 Interests an Gradients-- continue What happens upon receiving an interest? What happens upon receiving an interest? 1-If no matching entry exists, the node creates an interest entry. The parameters of this entry are instantiated from the received interest. ( neighbors must be distinguished, 802.11 MAC addresses, Bluetooth cluster addresses. 1-If no matching entry exists, the node creates an interest entry. The parameters of this entry are instantiated from the received interest. ( neighbors must be distinguished, 802.11 MAC addresses, Bluetooth cluster addresses. 2- If there exist an entry, but no gradient for the sender, the node add a gradient of the specified value. It also updates the timestamp and duration fields 2- If there exist an entry, but no gradient for the sender, the node add a gradient of the specified value. It also updates the timestamp and duration fields 3-If there exist an entry and gradient, the node only updates the timestamp and duration fields.

15. 3.2 Interests an Gradients-- continue When a gradient expires, it is removed from the entry. Not all gradients will expire at the same time. (i.e. if two different sinks posts indistinct interests with different expiration time, some node in the network may have gradients with different expiration time. When a gradient expires, it is removed from the entry. Not all gradients will expire at the same time. (i.e. if two different sinks posts indistinct interests with different expiration time, some node in the network may have gradients with different expiration time. When all gradients for an interest is removed, the interest entry itself is removed from the cache. When all gradients for an interest is removed, the interest entry itself is removed from the cache. Why gradients are removed and how it is done is discussed in 3.3. Why gradients are removed and how it is done is discussed in 3.3.

16. 3.2 Interests an Gradients-- continue Upon receiving an interest, the node may decide to re-send it to its neighbors. The interest appears to originate from the sending node, not the original sink. This is called local interaction. Upon receiving an interest, the node may decide to re-send it to its neighbors. The interest appears to originate from the sending node, not the original sink. This is called local interaction. Not all received interest are re-sent. A node may no re-send a received interest if it is recently re-sent a matching interest. Not all received interest are re-sent. A node may no re-send a received interest if it is recently re-sent a matching interest.

17. 3.2 Interests an Gradients-- continue How to choose a neighbor? How to choose a neighbor? 1-Re-broadcasting the interest to all neighbor. This is the only choice in the absence of information about which node will satisfy the interest. 1-Re-broadcasting the interest to all neighbor. This is the only choice in the absence of information about which node will satisfy the interest. 2-It is possible to use geographic routing. This can limit the scope of interest diffusion. This yields to energy saving. 2-It is possible to use geographic routing. This can limit the scope of interest diffusion. This yields to energy saving. 3-In immobile sensor networks, nodes may use data cache to direct interests. (i.e. If the node heard that neighbor A sent data in response to an earlier interest, the node may sent the interest to A rather than broadcasting to all neighbors. 3-In immobile sensor networks, nodes may use data cache to direct interests. (i.e. If the node heard that neighbor A sent data in response to an earlier interest, the node may sent the interest to A rather than broadcasting to all neighbors.

18. 3.2 Interests an Gradients-- continue Notice that in figure2(a ), every pair of neighbors establishes a gradients towards each others. Notice that in figure2(a ), every pair of neighbors establishes a gradients towards each others. How local interaction is the reason for this? How local interaction is the reason for this? When a node receives an interest from its neighbor, it doesn’t know whether this interest was in response to an interest it sent out earlier or identical interest from another sink I the other side of that neighbor. This cause each node to receive one copy of the low data rate events from its neighbors. This technique can enable fast recovery from failed paths or reinforcement of better paths. Doesn't incur persistent loops. This technique can enable fast recovery from failed paths or reinforcement of better paths. Doesn't incur persistent loops.

19. 3.2 Interests an Gradients-- continue A gradient specifies both, a data rate and direction. A gradient specifies both, a data rate and direction. More generally a gradients specifies a value and direction. The designer have the freedom to attach different semantics to gradients values. More generally a gradients specifies a value and direction. The designer have the freedom to attach different semantics to gradients values.

20. 3.3 Data propagation Upon receiving an interest, the node tasks its sensors to start collecting data. Upon receiving an interest, the node tasks its sensors to start collecting data. Comparison with pre-sampled waveforms. Comparison with pre-sampled waveforms. When detecting a target, the node searches its interest cache for a matching interest (described later). When finding one, it starts to generate event at highest data rate among all of its gradients. When detecting a target, the node searches its interest cache for a matching interest (described later). When finding one, it starts to generate event at highest data rate among all of its gradients.

21. 3.3 Data propagation--continue A node that receives a data attempts to find a matching entry (i.e. the same rect and the same type of the entry). A node that receives a data attempts to find a matching entry (i.e. the same rect and the same type of the entry). Finding a matching interest entry for the received data; Finding a matching interest entry for the received data; 1-No match exists, the data is dropped. 1-No match exists, the data is dropped. 2-A match exists, the node checks the data cache associated with the interest. (it tracks the recently seen data items for several purposes, one of them is loop prevention). If there exist a matching data in the data cache, the data is dropped. 2-A match exists, the node checks the data cache associated with the interest. (it tracks the recently seen data items for several purposes, one of them is loop prevention). If there exist a matching data in the data cache, the data is dropped. 3-No matching data, the data is stored in the data cache and re-sent to the node’s neighbors.

22. 3.3 Data propagation--continue At what rate must the received data be re-sent? At what rate must the received data be re-sent? 1-If all gradients data rate is greater than or equal to the rate of received events, the received data message will be re-sent to appropriate neighbors. 2-If some gradients have lower data rate than others (caused by reinforcement, section 3.4), then the node may downstream to appropriate neighbor.

23. 3.4.1 Reinforcement When he source detects a target, it send the data along multiple paths. When the sink receives this low data rate events, it reinforces one neighbor to “draw down” higher quality events (higher data rates). When he source detects a target, it send the data along multiple paths. When the sink receives this low data rate events, it reinforces one neighbor to “draw down” higher quality events (higher data rates). The reinforcements is done according “data driven” local rules (i.e. reinforce the neighbor from which it receives previously unseen event. The reinforcements is done according “data driven” local rules (i.e. reinforce the neighbor from which it receives previously unseen event. The reinforcement is done by The reinforcement is done by re-sending the original interest re-sending the original interest but with higher a smaller interval. but with higher a smaller interval.

24. 3.4.1 Reinforcement--continue When the neighboring node receives this smaller-interval interest. If the data rate is higher than that of any existing gradients, it must reinforce at least one neighbor. When the neighboring node receives this smaller-interval interest. If the data rate is higher than that of any existing gradients, it must reinforce at least one neighbor. How this reinforcement done? How this reinforcement done? The node uses its data cache. The same local rules applies. The node may choose a neighbor from whom it received the latest event matching the interest. May also reinforce all neighbor form which new events (low data rate events) were recently received. By this sequence of local interactions, a path of higher data rates is established from the source the sink. By this sequence of local interactions, a path of higher data rates is established from the source the sink.

25. 3.4.1 Reinforcement--continue The mechanism described above is very reactive to changes in path quality. When one path delivers data faster than others, the sink attempts to reinforce this new path, which could be wasteful for resources. The mechanism described above is very reactive to changes in path quality. When one path delivers data faster than others, the sink attempts to reinforce this new path, which could be wasteful for resources. To solve this problem, more sophisticated local rules are possible. Such rules may be, reinforce the node that most events have been received from. Also, reinforce the node the deliver events before another nodes. To solve this problem, more sophisticated local rules are possible. Such rules may be, reinforce the node that most events have been received from. Also, reinforce the node the deliver events before another nodes.

26. 3.4.2 Negative Reinforcement The algorithm used above may result in more than one path. Consider that the sink reinforces A, then received a new event from B, it will reinforce B. If the path through B is better, the sink needs a mechanism to negatively reinforce the path through A. The algorithm used above may result in more than one path. Consider that the sink reinforces A, then received a new event from B, it will reinforce B. If the path through B is better, the sink needs a mechanism to negatively reinforce the path through A. One of the mechanisms of negative reinforcement is to time out all high data rate gradients unless they are explicitly reinforced. This need the sink to periodically reinforce the neighbor B, and cease reinforcing neighbor A. This will degrade the path through A. Another approach is to explicitly degrade the path through A by re-sending interests at lower data rates. One of the mechanisms of negative reinforcement is to time out all high data rate gradients unless they are explicitly reinforced. This need the sink to periodically reinforce the neighbor B, and cease reinforcing neighbor A. This will degrade the path through A. Another approach is to explicitly degrade the path through A by re-sending interests at lower data rates.

27. 3.4.2 Negative Reinforcement-- continue When A receives this lower data rate interest, it degrades its gradients toward the sink. When all its gradients are now low data rate, A negatively reinforce those neighbors that have been sending data to it at higher data rates. The local interaction ensures that the path through A is degraded rapidly, but the cost is in the increase in resource utilization. When A receives this lower data rate interest, it degrades its gradients toward the sink. When all its gradients are now low data rate, A negatively reinforce those neighbors that have been sending data to it at higher data rates. The local interaction ensures that the path through A is degraded rapidly, but the cost is in the increase in resource utilization.

28. 4- Performance

29. 4- Performance--continue