A system for distributed computation in a communication network, the system comprising: a processor; a memory coupled to the processor, wherein the memory comprises a plurality of modules capable of being executed by the processor, and wherein the plurality of modules comprising: a cluster monitoring module configured to receive data for computation; a privacy module configured to provide privacy measurement by performing sensitivity analysis on computation capability of a plurality of edge devices and sensitive content of the data, wherein the privacy measurement is based on the computation capability of the plurality of edge devices; and segregate the data into smaller data sets and apply a privacy preservation mechanism based on the privacy measurement of the data; and a communication module configured to transfer the data to the plurality of edge devices for efficient load distribution during computation and to preserve privacy; and optimize bandwidth usage and energy consumption during the transfer of the data over the communication network, wherein the bandwidth usage and energy consumption are optimized by compressing the data by network encoding the data prior to the transfer of data, and preserving a relation between the length of coded data and the number of edge devices receiving the data. a processor; a memory coupled to the processor, wherein the memory comprises a plurality of modules capable of being executed by the processor, and wherein the plurality of modules comprising: a cluster monitoring module configured to receive data for computation; a privacy module configured to provide privacy measurement by performing sensitivity analysis on computation capability of a plurality of edge devices and sensitive content of the data, wherein the privacy measurement is based on the computation capability of the plurality of edge devices; and segregate the data into smaller data sets and apply a privacy preservation mechanism based on the privacy measurement of the data; and a communication module configured to transfer the data to the plurality of edge devices for efficient load distribution during computation and to preserve privacy; and optimize bandwidth usage and energy consumption during the transfer of the data over the communication network, wherein the bandwidth usage and energy consumption are optimized by compressing the data by network encoding the data prior to the transfer of data, and preserving a relation between the length of coded data and the number of edge devices receiving the data. a cluster monitoring module configured to receive data for computation; a privacy module configured to provide privacy measurement by performing sensitivity analysis on computation capability of a plurality of edge devices and sensitive content of the data, wherein the privacy measurement is based on the computation capability of the plurality of edge devices; and segregate the data into smaller data sets and apply a privacy preservation mechanism based on the privacy measurement of the data; and provide privacy measurement by performing sensitivity analysis on computation capability of a plurality of edge devices and sensitive content of the data, wherein the privacy measurement is based on the computation capability of the plurality of edge devices; and segregate the data into smaller data sets and apply a privacy preservation mechanism based on the privacy measurement of the data; and a communication module configured to transfer the data to the plurality of edge devices for efficient load distribution during computation and to preserve privacy; and optimize bandwidth usage and energy consumption during the transfer of the data over the communication network, wherein the bandwidth usage and energy consumption are optimized by compressing the data by network encoding the data prior to the transfer of data, and preserving a relation between the length of coded data and the number of edge devices receiving the data. transfer the data to the plurality of edge devices for efficient load distribution during computation and to preserve privacy; and optimize bandwidth usage and energy consumption during the transfer of the data over the communication network, wherein the bandwidth usage and energy consumption are optimized by compressing the data by network encoding the data prior to the transfer of data, and preserving a relation between the length of coded data and the number of edge devices receiving the data.