In the field of embedded systems, computers embedded into machines ranging from microwaveovensto assembly lines impact the physical world. They do so under tight real-time constraintswith ever-increasing demand for computing power and performance. Development of higher speedprocessors have been hampered by diminishing returns on power consumption as clock frequency isfurther increased. For this reason, today, embedded processor development is instead moving towardfurther concurrency with multi-core processors being considered more and more every day. Withparallelism comes challenges, such as interference caused by shared resources. Contention betweenprocessor cores, such as shared memory, result in inter-core interference which is potentially unpredictableand unbounded. The focus of this thesis is placed on minimizing inter-core interferencewhile meeting local task timing requirements by utilizing scheduling heuristics. A scheduling heuristicis designed and a prototype scheduler which implements this algorithm is developed. Thescheduler is evaluated on randomly generated test cases, where its ability to keep inter-core datapropagationdelays low across different core counts and utilization values was evaluated. The algorithmis also compared with constraint programming in a real world industrial test case. Theobtained results show that the algorithm can produce schedules with low inter-core delays in a veryshort time, although not being able to optimize them fully compared to constraint programming.