International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 05 | May -2017
p-ISSN: 2395-0072
www.irjet.net
Live Code Update for IoT Devices in Energy Harvesting Environments Raksha S1, Sushmitha K1, Deepika B1, Ganavi N1, Chandini S B2 1Student,
2Assistant
Dept. of Information Science and Engineering, VVCE, Mysuru, Karnataka, India Professor, Dept. of Information Science and Engineering, VVCE, Mysuru, Karnataka, India
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Abstract - There is a rapid rise in growth exhibited by
It is obvious that, IoT devices may need software updates to fix bugs, add functionality, or improve computational capability. So how to deliver code updates to the energy harvesting devices post-deployment is another critical concern. This project proposes novel strategies to update deployed code for IoT energyharvesting devices based on in-place code updating.
number of Internet of Things (IoT) devices. IoT devices is usually connected with the physical world. These devices may harvest energy as a power source, which inflict particularly rigid operating restrictions. In addition IoT devices may need software updates to fix bugs, add functionality, or input computational capability. This paper proposes in-place code updating to update deployed code for IoT energy harvesting devices. This strategy applies patches in-place while the code is still running and active; which competently eliminate system down time and reduce resource demands for updates.
Our objective is to propose a novel in-place patching strategy for the three code update scenarios of insertion, deletion, and modification that minimizes the down time of a device. We aim to develop strategies on device down time, code update delivery cost, code memory update cost, and runtime performance overhead.
Key words: Live Code, Live code Update for IoT devices, IoT devices, Energy Harvesting Environments, Live Code for IoT devices.
2. EXISTING SYSTEM
1. INTRODUCTION
Currently post-deployment code update schemes focus mainly on reducing the amount of data transferred over the wireless network. This includes proposals involving naïve, incremental updates, modular designs, and network encoding. These incremental update schemes attempt to minimize the code transferred to a device by sending only the “delta” difference between the old and new images, instead of sending the entire image. The new image then is constructed from the old image and the delta [2], [3], [4], [5], [6].
Internet of Things (IoT) is an ecosystem of connected physical objects that are accessible through the internet. The ‘thing’ in IoT could be a person with a heart monitor or an automobile with built-in-sensors, i.e. objects that have been assigned an IP address and have the ability to collect and transfer data over a network without manual assistance or intervention. The embedded technology in the objects helps them to interact with internal states or the external environment, which in turn affects the decisions taken.
These approaches have the following steps:
The Internet of Things (IoT) is a novel computing paradigm that couples sensing devices, computing nodes, communication devices with various types of objects in physical world for data collection, exchange, and remote control. IoT devices often have very tight constraints on cost, form factor, and power/energy consumption. These devices often rely on ambient power sources such as wireless energy, RF energy, solar energy, and piezoelectric energy.
transmit the code update, construct a new image if the code update was a delta, and Reboot the device using the new code image. This approach is called image rewrite. This method has several limitations.
The ambient power is not only scanty but also often unreliable. This makes it necessary to equip these devices with non-volatile memory to store program state in order to ensure forward progress. Often state has to be stored and only a couple of instruction can be executed per power cycle [1].
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QOS level of the device is degraded. Rebooting and re-launching is required during which it is unresponsive to external events. This delay is down time of the device [7], [8]. It takes longer for code updates to be delivered to devices because existing image rewrite approaches do not work well with incremental updating.
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