Google Glass Development: Performance Tips

Google glass performance

Google glass performance

With google glass development, performance has to take center stage and software engineers, no more can afford to put performance testing on back burner. Following are some of the techniques for achieving high performance of glasswares:

  1. Compression (to beat Network Latency): Compression technique has been one of the most important aspect in getting faster download of your web pages. The primary reason have been to take care of network latency aspects which would impact glasswares performance much more. You may want to check the details on this on following page. The same technique also applies to google glasswares by enabling gzip compression. One needs to do following two things to achieve gzip compression by setting following in HTTP headers:
    1. Accept-Encoding: gzip
    2. User-Agent: my program (gzip)
  2. Partial Data (to optimize CPU/Memory/Network Resources): Partial data (enough data) is achieved by sending & receiving the minimum data for request/response to be completed: This may be termed as partial response and partial update (patch). The objective is to reduce the activities of network, CPU, memory by avoiding transferring unnecessary data (network), transfer/process data (cpu), and store them (memory). Following are two different kinds of partial requests:
    1. Partial Response: Send information about the enough fields that is needed in HTTP response. This would let server send only enough data in form of partial response.
    2. Partial Update (Patch): Send only the enough data in Http update request, that needs to be updated.


Ajitesh Kumar
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Ajitesh Kumar

I have been recently working in the area of Data Science and Machine Learning / Deep Learning. In addition, I am also passionate about various different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia etc and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc. I would love to connect with you on Linkedin.
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