Service and Resource Discovery in Smart Spaces Composed of Low Capacity Devices



Similar documents
Internet of Things 2015/2016

Demystifying Wireless for Real-World Measurement Applications

A Transport Protocol for Multimedia Wireless Sensor Networks

JoramMQ, a distributed MQTT broker for the Internet of Things

VXLAN: Scaling Data Center Capacity. White Paper

Thingsquare Technology

SAN/iQ Remote Copy Networking Requirements OPEN iscsi SANs 1

SIP Protocol as a Communication Bus to Control Embedded Devices

Key requirements for Interoperable IoT systems

Data Management in Sensor Networks

APPENDIX 1 USER LEVEL IMPLEMENTATION OF PPATPAN IN LINUX SYSTEM

Attenuation (amplitude of the wave loses strength thereby the signal power) Refraction Reflection Shadowing Scattering Diffraction

Using IPv6 and 6LoWPAN for Home Automation Networks

Achieving Nanosecond Latency Between Applications with IPC Shared Memory Messaging

Introduction to Routing and Packet Forwarding. Routing Protocols and Concepts Chapter 1

A Systems of Systems. The Internet of Things. perspective on. Johan Lukkien. Eindhoven University

LoRaWAN. What is it? A technical overview of LoRa and LoRaWAN. Technical Marketing Workgroup 1.0

6LoWPAN Technical Overview

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

WAN Data Link Protocols

In-Vehicle Networking

Voice over IP. Demonstration 1: VoIP Protocols. Network Environment

IPv6 Challenges for Embedded Systems István Gyürki

Figure 1. The Example of ZigBee AODV Algorithm

High-Frequency Distributed Sensing for Structure Monitoring

Network Simulation Traffic, Paths and Impairment

HP LeftHand SAN Solutions

Software design (Cont.)

Performance Analysis of IPv4 v/s IPv6 in Virtual Environment Using UBUNTU

10 Gbps Line Speed Programmable Hardware for Open Source Network Applications*

Portable Wireless Mesh Networks: Competitive Differentiation

Resource Utilization of Middleware Components in Embedded Systems

PEDAMACS: Power efficient and delay aware medium access protocol for sensor networks

EINDHOVEN UNIVERSITY OF TECHNOLOGY Department of Mathematics and Computer Science

An experimental test bed for the evaluation of the hidden terminal problems on the IEEE standard

Performance Evaluation of AODV, OLSR Routing Protocol in VOIP Over Ad Hoc

Management of VMware ESXi. on HP ProLiant Servers

UPnP-Based Sensor Network Management Architecture

The proliferation of the raw processing

INTRODUCTION TO WIRELESS SENSOR NETWORKS. Marco Zennaro, ICTP Trieste-Italy

Internet of Things based approach to Agriculture Monitoring

Customer Specific Wireless Network Solutions Based on Standard IEEE

M2M I/O Modules. To view all of Advantech s M2M I/O Modules, please visit

The new frontier of the DATA acquisition using 1 and 10 Gb/s Ethernet links. Filippo Costa on behalf of the ALICE DAQ group

Safeguards Against Denial of Service Attacks for IP Phones

Wireless Sensor Networks Chapter 3: Network architecture

Internet of things (IOT) applications covering industrial domain. Dev Bhattacharya

Performance Evaluation of VoIP Services using Different CODECs over a UMTS Network

ZEN LOAD BALANCER EE v3.04 DATASHEET The Load Balancing made easy

An Introduction to VoIP Protocols

Definition. A Historical Example

PANDORA FMS NETWORK DEVICE MONITORING

UAVNet: Prototype of a Highly Adaptive and Mobile Wireless Mesh Network using Unmanned Aerial Vehicles (UAVs) Simon Morgenthaler University of Bern

ZEN LOAD BALANCER EE v3.02 DATASHEET The Load Balancing made easy

Figure 1.Block diagram of inventory management system using Proximity sensors.

SmartDiagnostics Application Note Wireless Interference

INTERNET OF THE THINGS (IoT): An introduction to wireless sensor networking middleware

Secure data aggregation in mobile sink wireless sensor networks

HIPAA Security Considerations for Broadband Fixed Wireless Access Systems White Paper

CROSS LAYER BASED MULTIPATH ROUTING FOR LOAD BALANCING

PANDORA FMS NETWORK DEVICES MONITORING

CHAPTER 6. VOICE COMMUNICATION OVER HYBRID MANETs

DT-WBAN: Disruption Tolerant Wireless Body Area Networks in Healthcare Applications

A Link Load Balancing Solution for Multi-Homed Networks

VOIP over Space Networks

SPINS: Security Protocols for Sensor Networks

M 2 M IWG. Eclipse, M2M and the Internet of Things. Overview. M 2 M Industry WorkGroup! M2M?

Outline. Institute of Computer and Communication Network Engineering. Institute of Computer and Communication Network Engineering

COMMUNICATION NETWORKS WITH LAYERED ARCHITECTURES. Gene Robinson E.A.Robinsson Consulting

CHAPTER 6 SECURE PACKET TRANSMISSION IN WIRELESS SENSOR NETWORKS USING DYNAMIC ROUTING TECHNIQUES

Design and Performance Analysis of Building Monitoring System with Wireless Sensor Networks

Objectives. Distributed Databases and Client/Server Architecture. Distributed Database. Data Fragmentation

packet retransmitting based on dynamic route table technology, as shown in fig. 2 and 3.

A Middleware for OSCAR and Wireless Sensor Network Environments

Cloud Operating Systems for Servers

Computer Network. Interconnected collection of autonomous computers that are able to exchange information

Wireless Home Networks based on a Hierarchical Bluetooth Scatternet Architecture

Quantifying the Performance Degradation of IPv6 for TCP in Windows and Linux Networking

Automatic Configuration and Service Discovery for Networked Smart Devices

TE in action. Some problems that TE tries to solve. Concept of Traffic Engineering (TE)

in Health Care and Sensor Networks

Managing Mobile Devices Over Cellular Data Networks

Final for ECE374 05/06/13 Solution!!

RT-QoS for Wireless ad-hoc Networks of Embedded Systems

Runtime Verification for Real-Time Automotive Embedded Software

Best Practices: Extending Enterprise Applications to Mobile Devices

Performance of Host Identity Protocol on Nokia Internet Tablet

Repeat Success, Not Mistakes; Use DDS Best Practices to Design Your Complex Distributed Systems

Ship to Shore Communications Management for MTN Satellite Communications Inc.

AdvOSS Session Border Controller

Introduction Page 2. Understanding Bandwidth Units Page 3. Internet Bandwidth V/s Download Speed Page 4. Optimum Utilization of Bandwidth Page 8

Extending Networking to Fit the Cloud

Transcription:

Service and Resource Discovery in Smart Spaces Composed of Low Capacity Devices Önder Uzun, Tanır Özçelebi, Johan Lukkien, Remi Bosman System Architecture and Networking Department of Mathematics and Computer Science Eindhoven University of Technology

Outline duction and Problem Description Proposed Solution Experimental Results Conclusions and

Smart Spaces Smart Space: a (living) space with embedded technology... regular CE & computing devices smart nodes: sensing, actuating, communicating, computing...that is networked... wireless, mostly...designed to collaborate and share...... to interact with / serve users... maximum autonomous operation provide services with minimal user effort... and the electronics these users carry e.g. body sensor networks, personal electronics

Low Capacity Devices Sample specifications: CPU: 1-25 MHz clock frequency 1-10 kilobytes of RAM / 1-128 kilobytes of programmable ROM Communication device: Frequency band 433 MHz 2.4 Ghz 2.0 2.5 Ah for an AA size battery perhaps much smaller even sensors, actuators Example: Wireless Sensor Network networks of cheap and intelligent sensors. Representative of low-capacity device class Naturally pervasive: automatic operation, seamless integration, collaboration but: little energy and: small packet sizes, bit rates

Smart Space Architectures Many SS architectures are heavy-weight! layered architectural design for the sake of abstraction (suboptimal) messaging overheads, increased energy usage. State-of-the-art frameworks (e.g. OSGi, NoTA-M3) have high resource requirements. Execution platform, message (xml) size and interpretation overhead Implicit assumption: SS network is composed of relatively high capacity nodes (e.g. laptop computers, mobile phones, PDAs). Unusable directly with low capacity nodes (e.g. WSN nodes) energy, computational power, network bandwidth limitations. needs gateways/proxies configuration overhead, reliability latencies

Fundamental requirements Smart Space requirements programmable and configurable wished behavior can be imposed sharing of services by concurrent (distributed) applications separation of coordination and service separate application logic from device functions integration with the regular IP infra structure Basic functionalities provided by nodes to the network Code load to define services, configuration Discovery - detection of nodes, services, resources Service/Resource Monitoring & Management Service composition/coordination by third party Lightweight architecture: how to provide this with low-capacity nodes? This work focuses on example of service/resource discovery and monitoring: Node is discovered (registered to the system) Node is monitored (report introspection information)

Outline duction and Problem Description Proposed Solution Experimental Results Conclusions and

Baseline Architecture: OSAS Framework Open Service Architecture for Sensors (OSAS) language, to program the entire network ( macroprogramming ) with concepts of a service, eventing and subscription and content-based addressing runtime system contains virtual machine (byte code) has access to a set of system calls (OS-provided functions) message format Four components Compiler Loader Runtime system Simulator runs same runtime system Gateway

OSAS Framework: Programming Model Nodes run services: A service has event generators and event handlers. A link between a generator and a handler is called a subscription. Interaction between services by a asynchronous remote procedure call upon firing of the event or simply as part of a handler Supported by WASP Service Composition Language (WaSCoL) Specification of services with event-condition-action rules Composition of services (i.e. subscriptions) Use content-based addressing to associate node with service Programs can be developed and loaded incrementally

Run-time organization 15-Feb-10 10

Connection by subscriptions subscription, defines sampling rate and remote handler to call 15-Feb-10 11

OSAS Framework: Messaging and Communication Communication: SendToSubscribers(), in case event fires Send() i.e. arpc in local neighbordhood Two implicit routing methods: Flooding, to transmit installation messages Point-to-point: route is setup via a subscription application-level routing Message format asynchronous remote procedure call Header; (Handler, arguments) series can be bound to MAC, or other carriers (e.g. UDP)

Example: Smart Space Management Given: a network running an OSAS application A resource manager (RM, special node) wants to know which nodes exist which services these run and subscriptions they have which resources are available on these nodes memory, battery,... RM may make this information available again as a service, or use it for taking mapping decisions 15-Feb-10 13

Smart Space Management Architecture

Service/Resource Monitoring: Reporting Intervals & Triggers

Implementation Management functionality is implemented as (part of) an OSAS application Node discovery: RM regularly subscribes to a heartbeat service of all nodes (in fact: advertises itself in this way) result: RM receives regular heartbeat indicating nodes presence first is used to register node Path reconstruction due to mobility Regular subscription solves this RM may subscribe to specific node after some heartbeat misses or just reconstruct the route ( setroute ) Service & resource discovery: part of heartbeat response message frequency of resource reporting and service reporting as extra parameter of subscription, or as additional subscriptions RM may inject those services itself 15-Feb-10 16

Service Discovery & path maintenance - Periodic advertisement - Conditional route reconstruction

Outline Proposed Solution duction and Problem Description Proposed Solution Experimental Results Conclusions and Experimental Results

Example Scenario Example scenario with the following parameters: Parameter Value Proposed Solution HeartBeat Period Timeout Period Route Fix Trigger 1 second 6 seconds 3 seconds to timeout Experimental Results Max. Route Fix Frequency Refresh Registry Period Advertisement Period LowFrequencySubscription Period HighFrequencySubscription Period Triggering Conditions Check/Response Period every 3 seconds 1 second 10 seconds 60 minutes 30 seconds 1 second

Example Scenario: Messaging Calculations Proposed Solution Sent Messages Received Messages HeartBeat: 60 Advertisement: 6 Report Resources: 2 Resource Report Subscription: 2 Report Services: 1/60 Services Report Subscription: 1/60 Report Subscriptions: 1/60 Subscriptions Report Subscription: 1/60 Total: ~ 62 Total: ~ 8 Experimental Results Message Count of Regular Interval Messages (per minute) Sent Messages Received Messages Node Entry 3 3 Set Route 1 1 Node Departure 1 1 Service Mapping 2 2 Message Count of Triggering Conditions Messages (per occasion)

Deployment on Physical Nodes Proposed Solution Experimental Results ROM (in bytes) RAM (in bytes) TinyOS (w/o OSAS) 15912 947 TinyOS (w/ OSAS) 28068 1289 Footprint of TinyOS and OSAS Service Size (in bytes) HeartBeatService 28 (14 ROM + 14 RAM) ReportServicesService 30 (16 ROM + 14 RAM) ReportResourcesService 30 (16 ROM + 14 RAM) ReportSubscriptionsService 30 (16 ROM + 14 RAM) Total 118 (62 ROM + 56 RAM) Footprint of Smart Space Application

Deployment on Physical Nodes Proposed Solution Experimental Results Message header size: MAC protocol (10 bytes) OSAS messaging protocol (5 bytes) Message payload sizes (assuming 8-bit encoding): Message HeartBeat Report 2 HeartBeat Subscription 17 Services Report Resources Report Subscriptions Report Services Report Subscription 17 Resources Report Subscription 17 Subscriptions Report Subscription 17 Service Mapping 9 Service Request Subscription 17 Size (in bytes) 3 + (# services) 2 + 2 * (# resources) 2 + 4 * (# subscriptions)

Outline Proposed Solution duction and Problem Description Proposed Solution Experimental Results Conclusions and Experimental Results

Proposed Solution Experimental Results Conclusion Platform for Smart Spaces, as well as for general sensor networks powerful primitives with little overhead runtime platform Node discovery, Service Discovery and Resource monitoring as just another application Heartbeat protocol with enhancements small overheads, given the platform exists Service/Resource Monitoring: Classification of information types and reporting intervals-triggers Low footprint values, fully operational

Proposed Solution Experimental Results Multiple RMs that synchronize reliability, distributed control Reduce footprint further remove OS can reduce ROM with 10k, RAM with 0.8K Monitoring mechanism: Remove redundant information delivery. Timing durations set by individual nodes. Timing adjustments according to the dynamicity of the network. Management mechanism: Implement service recovery (remapping). Provide advanced service mapping and arbitration. Use aggregation to reduce #messages.