Self Configuring & Self Organizing Protocols

Self Configuring & Self Organizing Protocols Pallavi Unkule

Outline • Background. • Taxonomy of Sensor Network Applications. • Policy Decisions & Assumptions for the self-configuring architecture. • Terminology used. • Architecture for the self-configurable systems. • A Self-Organizing algorithm and its analysis. • References. Pallavi Unkule

Background Pallavi Unkule

Background • Why do we need self-organizing protocol? Wireless Sensor Networks are used in applications where • They are deployed in large numbers (hundreds or thousands of sensor nodes). • They are deployed in remote/hostile environment. • Systems in which sensor nodes need to self-organize themselves into a network belong to the class of self configurable systems. Pallavi Unkule

Terminology Pallavi Unkule

Terminology • Sensor Motes • Sensor node that performs data discovery • Sink Node • Node with high processing capabilities and high capacity for data storage • Specialized Sensor • Sensor that performs specific data discovery operation (e.g. temperature sensors) • Router Sensor • Router sensor – collects and transmits data to neighbors Pallavi Unkule

Terminology • High-End System • Sink node • 2-Connected Graph • Topology in which there are two edge disjoint paths from every node to every other node • Broadcast Graph • Subset of edges in the network used for broadcasting data • Directed Acyclic Graph (DAG) • Graph with directed edges and no cycles Pallavi Unkule

Taxonomy of Sensor Network Applications Pallavi Unkule

Taxonomy of Sensor Network Applications • Classifying sensor network applications • Important Factors • Size of the system & number of sensors used • Determine effort needed to configure the system • Maximum distance of the sensors to the wired infrastructure • Determines the amount of intelligence required at a sensor for routing to specific high processing nodes • Distribution of the sensor nodes • Deterministic – administrator controls placement of sensor nodes and user performs remedial operations in case of faults • Non-deterministic – fault-tolerance level depends on number of sensors deployed Pallavi Unkule

Taxonomy of Sensor Network Applications • Three classifications of sensor network applications • Non-propagating systems • Sensor nodes are one hop to wired infrastructure • Wired infrastructure is the main connecting component • Nodes connected to the wired infrastructure route information to the end system Pallavi Unkule

Sensors Non Propagating Systems Boundary between wired and wireless infrastructure Taxonomy of Sensor Network Applications Wired Nodes Pallavi Unkule

Taxonomy of Sensor Network Applications • Deterministic routing systems • Sensor nodes route through a few hops to reach a wired infrastructure • Routes to the wired infrastructure are deterministic • Number of nodes in this system may be restricted Pallavi Unkule

Wired Nodes Sensors Boundary between wired and wireless infrastructure Deterministic Routing Systems Taxonomy of Sensor Network Applications Pallavi Unkule

Taxonomy of Sensor Network Applications • Self-configurable systems • Sensor nodes need to self-organize into a network • As long as the number of nodes in the system is small the systems are deterministic. • But when the number of nodes increase the systems become non-deterministic systems and they need to be self-configurable.(e.g. Security and Parking Lot networks) • Fault tolerance is achieved through re-configuring the system in the presence of new node and link failures Pallavi Unkule

Taxonomy of Sensor Network Applications Pallavi Unkule

Taxonomy of Sensor Network Applications • Non-Aggregating • Independent data • Transmitted separately • E.g. parking-lot systems • Aggregating • Data aggregating and transmitted along the network. • E.g. weather applications Self-configuring sensor networks should include the functionality of performing aggregation too. Pallavi Unkule

Policy Decisions & Assumptions for the Architecture of Self-configuring systems Pallavi Unkule

Policy Decisions & Assumptions • Heterogeneous nodes • Architecture should provide a common framework • Data Discovery & Data Dissemination • Two orthogonal components • Nodes that perform data discovery • Nodes that perform data dissemination Pallavi Unkule

Policy Decisions & Assumptions • Memory and Power Constraints • All nodes have memory and power constraints • Attempt to reduce state stored at every node • Employ energy aware routing • Application Specific Infrastructure Requirements • Infrastructure components is dependent on application • Provide a wide variety of features to allow the application to make use of what is required Pallavi Unkule

Policy Decisions & Assumptions • Mobility/Immobility of nodes • Data discovery nodes are mobile • Data dissemination nodes are stationary • Previous Works • Multi-functional nodes • Cost more to implement • Routing in highly specialized nodes wasting energy • Storage of mass information • Data-Centric Networking • Critical nodes need to keep large amounts of state information • Cut nodes can cause the data to be lost Pallavi Unkule

Policy Decisions & Assumptions • Self-Configurable systems require one or more of the following • Naming/Addressing System • Routing • Required to pass information to sensors with specific functionality • Unique addresses to every node required • Broadcasting • Required to pass information to every sensor in a network (e.g. a wakeup message to all nodes in a security network) • Multicasting Pallavi Unkule

Main Contribution of the Algorithm Pallavi Unkule

Main Contribution of the Algorithm • Scalability • Every node has a O(log n) bit unique identifier • Reduction of State and Localized Operations: • Maintain O(log n) + O(|N(v)|) state information at each node • N - # of nodes • V – current node • |N(v)| - # of neighboring nodes of v in network Pallavi Unkule

Main Contribution of the Algorithm • Power Efficiency and Reliable Paths • Keeps track of the power requirements at every node to compute reliable and power efficient paths • Hierarchical Routing Architecture • Nodes reorder themselves in a hierarchical structure • Size of routing table is reduced to O(log n) at every node Pallavi Unkule

Main Contribution of the Algorithm • Fault-Tolerant Broadcast Trees • Local Markov Loops (LML) technique is used to achieve fault tolerance • Reduce Frequency of Updates • Define discrete power levels to reduce the number of dynamic cost updates that need to be performed in the network Pallavi Unkule

Components&Infrastructure Pallavi Unkule

Components • Sensors • Specialized • Identifies itself with a class • Can communicate with other sensors either of its own class or with some other class • Can be Mobile • Routing • Form the backbone of the sensor network • Immobile • Performs data-dissemination Pallavi Unkule

Components • Advantages • Separation of dissemination and discovery • Shorter network hops – reduces power consumption • Cost decreased – routing sensors are not specialized and may cost less • Large amounts of routers can increase the fault tolerance of the system Pallavi Unkule

Components • Other components • Sink Nodes • High storage capacity & high processing power • Can connect to WAN • Can activate specific actuators (through messaging) and broadcast important messages into the sensor net. • Aggregator Nodes • Nodes with the functionality of aggregation; can be introduced in router nodes or specialized nodes • E.g. In weather monitoring application aggregation functionality is placed on all router nodes Pallavi Unkule

Infrastructure Components • Functionalities provided by this architecture • Unique address for all nodes • Routing information between two nodes • Fault-Tolerant broadcasting infrastructure • Broadcasting information within a certain radius • Multicasting information to specialized nodes • Self-reorganization in the face of node failures and network partitions Pallavi Unkule

Infrastructure Components • Scenarios in which these components are used • Security Sensors • Unique Addresses to pass critical information to that sensor • Routing Architecture to send messages to sink nodes • Multicasting infrastructure to coordinate actions of specialized sensors of a particular class • Broadcast infrastructure to alert all nodes within a radius to prepare to perform important actions Pallavi Unkule

Infrastructure Components • Parking-Lot Networks • Unique Addressing to isolate a particular node controlling a particular spot • Routing Infrastructure for routing messages • Broadcast Infrastructure not generally required but may be utilized Pallavi Unkule

Infrastructure • Addressing Infrastructure • If non-addressable nodes (e.g. traffic monitoring along a highway) • Self-configurable systems is an aggregating system • If addressing required - Local Unique Addressing • IP not appropriate – global unique addressing • An alternative solution • An alternative solution for addressing - MAC Layer • Ensure that every node has a unique MAC address. Pallavi Unkule

Infrastructure • Routing Infrastructure • Specialized nodes must be adjacent to a router • Transmits all messages to adjacent router with a message header • Indicates which node(s) to transmit the message to (whether to one node or broadcast or multicast) • Router acts as the proxy for the specialized node(s) i.e. every specialized node is addressed with the help of a router node. Pallavi Unkule

Infrastructure • Broadcast and Multicasting Infrastructure • Sensor networks are more data centric • Require broadcasting and multicasting of data to all or groups of sensor nodes • Fault Tolerant Broadcast tree is created • Changes developing Local Markov Loops (LML) • Directed Acyclic Graphs (DAG) are used to support fault tolerance in paths • Participants • Router sensors self-configure • Specialized sensors keep track of the nearest router sensors Pallavi Unkule

Self-Organizing Algorithm Pallavi Unkule

Self-Organizing Algorithm Phases of the algorithm • Discovery Phase • Organization Phase • Maintenance Phase • Self-Reorganization Phase Pallavi Unkule

Discovery Phase • Each node discovers its set of neighbors and fixes its maximum radius of data transmission • Criteria: • Nodes should not have too many neighbors • Specialized nodes n(x) =1 • Router nodes, n(x) > 1 where n(x) is the number of neighbors for node x • Maximum bound on transmission radius • Each node x picks a small radius r and broadcasts a Hello message indicating whether it is a router or a special node Pallavi Unkule

Discovery Phase • Every node within radius r replies back with a I am Here message and their coordinates (determined by GPS) • If # of replies < minimum threshold n(x), x broadcasts Hello over radius kr, for k > 1 • Repeat until # of nodes N that replies satisfies n(x) N  N(x) where n(x) and N(x) denote the min and max number of neighbors to node x. • Note that specialized nodes are only connected to routers only. Pallavi Unkule

Discovery Phase Hello r Pallavi Unkule

Discovery Phase I am here r Pallavi Unkule

Discovery Phase Hello kr Pallavi Unkule

Discovery Phase I am here kr Pallavi Unkule

Organization Phase • Network is organized as follows: • Nodes are aggregated into groups • Groups are aggregated into larger groups to form a hierarchy of groups which is height balanced • Each node is allocated an address based on its position in the hierarchy • A routing table of O(log n) is computed for each node • A broadcast tree and graph spanning all nodes is constructed • Graph is converted into a DAG based on the source node in the network Pallavi Unkule

Organization Phase • Group formation • Routers form small basic groups with neighbors found • Group size is restricted to 8 and each node in a group is allocated a 3-bit address. • Each node belongs to one basic group • Each node maintains the distance and the next hop for reaching every other node in the group • If a node is unable to join a group • It forms a one node group with address 000 •  is the height difference parameter. Pallavi Unkule

Organization Phase • Merging of Groups Assume 2 groups G1 and G2 with m & n bit address. For the formation of hierarchy set the value of  to 3 equal to the height of a basic group. • If m-n   the G1 and G2 are merged to G with • 0 appended to all node addresses in G1 • 1 appended to all node addresses in G1 • If m-n >  then • Consider node x in G1 with address (x1, x2, …xm) • Consider subgroup Hi in G1 with 1st i bits equal to (x1, x2, …xi) for i  m-n-1. • All nodes in Hi are connected. Pallavi Unkule

Organization Phase • Find if Hm-n-1 has a sub-branch where G2 can be added to hierarchy without affecting Height of Hm-n-1or G2. • If not able to merge them at any value of i, then merge them according to the 1st method and mark the new graph as height imbalanced. • A boundary node is a node that connects to a node in another group Pallavi Unkule

Organization Phase • Formation of hierarchy • Each Group G receives an advertisement from adjacent groups through it’s boundary nodes • Broadcast throughout the group • Contains size of adjacent group (# of address bits) • Each node concludes on an adjacent group G’ • G’ closest in size to G. • G’ has the maximum number of boundary nodes. then node of G sends a join message to G’. • If G’ decides to join G, the groups merge • Otherwise G selects the next best group H Pallavi Unkule

Organization Phase • Continue until all groups merge into one • At any point, If a group is heavily imbalanced, then the group is reorganized with an increased value of new = old + 1 • Theorem 1: Height of the hierarchy of the network will be O(log n) where n is the number of nodes in the graph Pallavi Unkule

Organization Phase • Perform group reorganization if necessary • If height is unbalanced at multiple levels, reorganize • Group is broken into sub-groups • Regroup without affecting the state of the rest of the network • Some routing tales of nearby nodes will have to change addresses of neighbors • Generate addresses for all nodes • To give a general picture, if  = 3, then every node in a network of 10000 nodes will have a 16 bit address. Pallavi Unkule

Self Configuring & Self Organizing Protocols