Distribution & Aggregation Technologies for SensIT 4/19/2017 Distribution & Aggregation Technologies for SensIT SensorWare and DSN Projects at UCLA

Two Projects: Distinct but Complementary SensorWare (RSC subcontract, start January 2000) Sensor Control Scripts lightweight, mobile, platform independent, secure target tracking application concept demonstration Distributed Middleware Services spatial addressing & communication (multicast, gathercast etc.) timing synchronization, fault management services DSN (ISI subcontract, start Oct 1999 with 1 student funding) Network protocol stack low-power and power-aware routing, MAC, and link protocols protocols for GPS-synchronized communication subsystem capability and attribute based addressing and connectivity partially leverage SensorWare spatial algorithms Network boot-up: discovery & distribution of location, capabilities Sensor network simulation and emulation leveraged by SensorWare

Introduction to the Project Teams SensorWare Mani Srivastava Miodrag Potkonjak CS faculty, co-PI Graduate students: Athanassios Boulis scripting environment Sascha Slijepcevic tracking with mobile scripts Scott Zimbeck node software Vlasios Tsiatsis (*) spatial addressing DSN Mani Srivastava Graduate students: Sung Park simulation platform Andreas Savvides MAC & routing Curt Schurgers power-aware routing Vlasios Tsiatsis (*) attribute based routing

Selected Work-In-Progress, Accomplishments, and Plans

Sensor Control Scripts [SensorWare] Desired capabilities rapid development and deployment of mission-specific sensor network applications allow transient users to access collective capabilities of sensor network in a mission-specific fashion go beyond the simple (static) query and response query as scripts, low latency customized tracking Approach scriptable, lightweight runtime system at each node compact and platform independent sensor node control scripts Node Object Model (sensor, SP, and communication) scripts can migrate (download, replicate), i.e. mobile modeled on systems with embedded runtime scripting environments to provides users access to system resources e.g. javascript (web servers and browsers) e.g. Tcl (routers, CAD tools, VxWorks RTOS, NS)

SensorWare Software Architecture Transient External User download Download migrate Sensor Scripts Sensor Node Hardware Hardware Abstraction Layer Node Kernel & APIs Sensor Scripts Middleware Applications APP SCRIPT SCRIPT Applications APP Node Kernel & APIs Sensor Middleware Hardware Abstraction Layer Sensor Node Hardware Sensor 1 Sensor 2

Implementation Approach Scripts based on subset of Tcl embeddable scripting language with portable interpreter RTOS/node resources & services visible as Tcl objects network protocol stack, signal processing stack, battery Model scripts express interest in RTOS events and messages events and messages put in a queue processed by handlers specified by script script can send, activate, and kill scripts at remote nodes Alternative organizations being evaluated single script per interpreter, all interpreters in a single process single script per interpreter, single interpreter per process

Scripting Environment Single Process Approach Variables HandlerFunc1 {} HandlerFunc2 {} . { {Event1 HandlerFunc1} {Event2 HandlerFunc2} } Interpreter #1 Interpreter #n script script App1 App1 Scheduler & Event Distributor Apps Script Manager Event Queue Script as FSM Sensor Object N/W Object Tcl Process Sensor Stack Network Stack Other Drivers/Services Base RTOS Hardware Abstraction Layer

Scripting Environment Multiple Process Approach { . wait e1 e2 if (e1=v1)… } Tcl Process #1 Interpreter script Event Queue Sensor Object N/W Object App1 Tcl Process #n Interpreter script Event Queue Sensor Object N/W Object App1 Apps Script Manager Free-form Script Sensor Stack Network Stack Other Drivers/Services Base RTOS Hardware Abstraction Layer

Plan and Status Implementation plan Status FY00 FY01 FY02 uC/OS on ARM processor in RSC nodes script-based target tracking application for demo in August no support for safety, security and authentication FY01 implementation on Win CE with support for Sensor.com nodes FY02 support for security, safety, and authentication Status port of basic Tcl interpreter to RSC node being debugged initial tracking algorithm using script model initial work on Tcl-ns link for rapid prototyping and testing

Tracking and Taxonomy of Queries Synchronous immediate reply Is there movement anywhere in the 2nd floor? Asynchronous establish a trigger Inform me whenever there is movement on the 2nd floor? Tracking continuous sampling Inform me of the location of the object every 10s

Mission-specific Tracking Using Sensor Scripts Resident application (or initial script flooded to all nodes) sends message to user informing a potential target User downloads a tracking script to the appropriate node script encodes a custom tracking mechanism, e.g. calculate new position every 10s and send it to user Script spreads to form an initial sensing cluster Script does data fusion or simple beamforming (using signal processing modules resident at the node) Script arranges for the active sensor cluster to “migrate” as the target moves motion prediction using history (e.g. movement direction) sentry scripts spawned around the cluster avoids polling and cluster management by the distant user

Tracking Scenario Tank @ x,y,z,t Region A Monitor Track Region A Tank 10s Monitor Region A

Tracking Scenario Region A Tank @ x,y,z,t

Tracking Scenario Region A Tank @ x,y,z,t

Tracking Scenario Region A Tank @ x,y,z,t

Relationship with Other Mobile Code Technologies Download new firmware (OS, apps) over the air RSC’s node allow this, useful for long timescale Penn State’s Reactive Sensor Network downloads executables and DLLs, identified by URLs, from repositories and their caches read/write data from URLs essentially, lookup service + Java’s applet model generalized to arbitrary executables and data general-purpose, heavyweight (no scripting) but may complement SensorWare environment can be used as the basis for search-and-fetch of modules needed by a SensorWare script, and for node initialization Mobile Streams in AGNI (Ranganathan) Mstreams not directly applicable, but underlying Tcl technology may be leveraged

Sensor Network Simulation & Emulation [DSN]

Sensor Network Simulation & Emulation [DSN] Accurate modeling of power consumption by the protocol stack and applications Modeling of sensors and targets creation of standard application scenarios for comparison of protocols Hybrid simulation/emulation network of “virtual” and “real” sensor nodes scalability studies with live sensor data easier debugging and development of protocol code “real” application on “virtual” nodes easier debugging and development of application code Approach: ns based

Power Modeling: ns-based Mobile Node in ns Mobile Sensor Node with Power Model Agent Agent Routing Sensor Routing Link Layer Link Layer Battery CPU Buffer Buffer MAC MAC with Power Management Baseband (Rate) RF (analog) Power Amplifier (PRF) PHY Model-aware PHY Node Model Channel Channel

Hybrid Simulation & Emulation monitor and control hybrid network (local or remote) real sensor apps on virtual sensor nodes app GUI app socket comm serial comm ns event gw Ethernet RS232 gateway Dll (RSC) V V R V V Gateway (Windows PC) R modified event scheduler Proxies for real sensor nodes Simulation Machine (Linux PC)

Status Accomplishments so far detailed radio model MAC layer with radio shutdown management low-power ad hoc routing protocol first generation hybrid capability (demonstration) routing layer and higher layers can be hybrid network with one real and n virtual nodes GUI to monitor the hybrid network Collaboration with Deborah Estrin’s group interest in UCLA’s more sophisticated energy consumption models for diffusion algorithm simulation they will incorporate UCLA’s models into standard ns release available to SensIT community

Power-aware Routing [DSN]

Power-aware Routing [DSN] Traditional power unaware multihop ad hoc routing protocols focus on fast topology changes metrics used: shortest hop, shortest delay, link quality, location stability, message & time overhead reduced node and network lifetime, and coverage power hot-spots power lost in signaling messages in quiescent state UCLA effort: routing protocols that focus on power power-based routing metrics leveraging location information during routing exploiting path diversity Intelligent combining of replies at intermediate nodes interaction between MAC and routing (TDMA MAC)

Power Metrics Considered Minimize energy consumed / packet large dissipation at selected bottleneck nodes just as with shortest path metric Maximize time to network partition important for sensor networks etc. load balance across the nodes in the cut-set difficult to implement Minimize variance in node power levels no single node is penalized, but difficult to implement Minimize cost / packet cost for a node reflects remaining battery life nodes “reluctance” to forward packets Minimize maximum node cost delay node failure and reduce variance in remaining battery lives

Accomplishments Evaluation of several power metrics with DSR significant extension of network lifetime (time to partition) Scheme to exploit path diversity for power idea is distribute traffic over alternative paths to increase network lifetime and coverage packet disperser and combiner entities Works with DSR as well as gradient based routing evaluation metrics time to breakdown, # of depleted nodes, RMS energy distribution problem: do not know which nodes are important as it depends on future target traffic pattern and user movement pattern

Path Diversity Scenario B C A user A and B generate 1 packet every 100 ms until 5s C generates 1 packet every 100 ms from 5s till 15s

# of Nodes with > 10% Battery Packets received by t=150: Normal: 127 Stochastic: 133 Energy Disperse: 160 Stochastic ED: 161 Divert streams: 175

RMS Battery Energy Consumption Lower Bound 2 Lower Bound 1

Intelligent Combining of Replies Target Target User User Naive Approach Better Approach

Other Accomplishment: Sensor Subsystem for ISI Platform [DSN] XC4013XLA FPGA 3.3v 64Kx16 Flash 128Kx8 SRAM A1-A16 D0-D15 ADC, 8ch Humidity 5v Angular Velocity 3D Accel Magnet- ometer 6v Microphone Speaker Light to Freq 2 2D Accel ADXL202 Freq 1 Temp2 Temp 1 I2C Bus 8:2 mux IR ENC/ DEC Serial Port TFDU IR RPC, 5V GPS D0-D7 A0 - A15 D8-D15 RS232 PC Serial Port 2 General purpose I/O lines 3.3V to 5V Transceiver Processor AT91M4040033AC JTAG DAC 8:1 mux UART 3.3v Amp Communications Analog Counter/Timer Ports Processing Digital XChecker PC Serial Port 1 GPS IR Light Sound in/out 2D accelerometer Temperature Magnetometer Angular velocity 3D accelerometer