Agent-based Device Management in RFID

Middleware

Author ： Zehao Liu, Fagui Liu, Kai Lin

Reporter ：郭瓊雯

Outline

IntroductionAgent technology in RFID device

management Device Configuration Management Device State Monitor Dynamic Job Scheduling

Conclusion and Future Work

2

Introduction

This paper proposes an agent-based device management approach in RFID middleware.

Authors design and implement two types of agents : Control Agent and Device Agent.

Through the collaboration of multiple agents, authors achieve the function of device management.

3

Introduction( 續 )

A device management approach based on agent technology : Providing a set of common operating interface

for RFID middleware. Supporting remote configuration and grouping

management of RFID devices. Monitoring the real-time state of devices. Dealing with unexpected events and carrying

out fault-tolerant processing. Schedule jobs for different devices

dynamically.4

Agent technology in RFID device management

5Figure ： Architecture of Device Management

Control Agent It is the core component, which manages all

Device Agents and maintains their life cycles.

It issues commands to the Device Agents, receives and analyzes the reply messages, and then makes decisions accordingly.

It controls the devices and makes them collaborate with each other to perform complex tasks.

6

Agent technology in RFID device management(con.)

Device Agent Each Device Agent is corresponding with a

physical device. It lies between the RFID middleware and the physical device.

Device Agent is composed of four components:

• Configuration module• Monitor module• Message module• Data management module

7

Agent technology in RFID device management(con.)

How to achieve complex device management tasks.

Device Configuration Management Device State Monitor Dynamic Job Scheduling

8

Agent technology in RFID device management(con.)

Device Configuration Management

Common Operating Interface It eliminates the heterogeneity of different

physical devices and provides a set of common operating interface based on the APIs provided by the major device manufacturers.

9

Device Configuration Management(con.)

Grouping Management It is carried out through the collaboration of

Control Agent and Device Agents. Control Agent provides a service to store and query the basic information of all Device Agents it controls. Every Device Agent registers the information of its associated physical device to Control Agent.

Control Agent maintains these information and searches for the specific devices if necessary.

10

Remote Configuration It is built on two bases.

• Common operating interface provided by Device Agent

• Communication mode based on XML messages between Device Agent and Control Agent.

User simply send a configuration command from the Control Agent to Device Agents to configure the physical devices without any manual interference with the remote hosts and devices.

11

Device Configuration Management(con.)

Remote Configuration

12Figure ： Device Configuration Procedure

Device Configuration Management(con.)

Device State Monitor

Each Device Agent monitors the running state of its associated device, deals with unexpected events, and collects related statistical data that are useful for the health of the device.

Device monitoring approach, author adopt two modes: Subscription mode Synchronous query mode

13

Device State Monitor(con.)

14

Figure ： Monitor Process

Dynamic Job Scheduling

In dynamic job scheduling mechanism, multiple Device Agents collaborate with each other, and the job of each reader device can be scheduled dynamically and separately, which greatly improves the work efficiency and the system performance.

15

Dynamic Job Scheduling(con.)

In most RFID application scenarios, a lot of RFID readers are deployed in different areas, such as the entrance and the exit in warehouse applications, to monitor the running state of these key areas.

According to the predefined process, the items attached by tags pass every reader one by one, so the amount of tags read in unit time and the time a tag is read are different for the readers deployed in different areas.

16

Dynamic Job Scheduling(con.)

Dynamic job scheduling mechanism is described as follows: 1)Suppose that N RFID readers are deployed in an

application scenario, each reader is denoted as Readeri, where i=1,2..N, and the device agent which is corresponding with Readeri is denoted as DeviceAgenti.

2)DeviceAgenti gathers statistical data according to the tag data read by Readeri, including the time each tag is read, the average time interval Ti that two consecutive tags are read by Readeri. Then DeviceAgenti sends these data to DeviceAgenti+1 periodically.

17

Dynamic Job Scheduling(con.)

3)When DeviceAgenti+1 receives the information coming from DeviceAgenti, it compares with its own statistical data, then calculates the average time required for a tag to move from Readeri to Readeri+1, denotes it as TSi.

4)Schedule jobs for different readers according to the historical data, Set the frequency of read cycles of Readeri to Ti, indicating that Readeri reads tags once every Ti time.

18

Dynamic Job Scheduling(con.)

5)When Readeri reads a tag, DeviceAgenti sends a notification to DeviceAgenti immediately. Upon receiving the notification, DeviceAgenti+1 sets a timer according to TSi so that Readeri+1 starts a read cycle when time’s up.

6)Repeat step 2 to 5 until system exits.

19

Test and Analysis

20

Test and Analysis(con.)

21

Table ： Performance Comparison ： shows the test result of SimulateReader2

Conclusion and Future Work

This paper proposes an approach for RFID device management based on agent technology according to the characteristics of agents and the requirements for device management in RFID middleware.

Control Agent and Device Agent are designed to achieve device management tasks.

22

Conclusion and Future Work(con.)

But the application scope of the dynamic job scheduling mechanism proposed in this paper is relatively narrow.

Author will study the dynamic job scheduling mechanism in depth and improve the algorithm so that it can be applied in more complex application scenarios.

Author can extend more functions on the basis of Device Agents, such as implementing load balancing in complex reader networks by coordinating multiple Device Agents.

23